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**EPA/635/R**

**- 14/378**  **Intera gency Review Draft**  **www.epa.gov/iris**



## Toxicological Review of tert

**- Butyl Alcohol (**  tert

**- butanol**  **)**

(CAS RN 75

- 65

- 0)

**In Support of Summary Information on the**  **Integrated Risk Information System (IRIS)**

**Supplemental Information** 

September 201 4

**NOTICE**

T his document is an **Interag ency**  **Science Consultation Review**  **Draft**

. This information is distributed solely for the purpose of pre

- dissemination peer review under applicable information quality guidelines. It has not been formally disseminated by EPA. It does not represent and should not be construed to represent any Agency determination or policy. It is being circulated for review of its technical accuracy and science policy implications.

Integrated Risk Information System National Center for Environmental Assessment Office of Research and Development U.S. Environmental Protection Agency Washington, DC

### Supplemental Information― tert

- Butanol

**DISCLAIMER**

This document is a preliminary draft for review purposes only. This information is distributed solely for the purpose of pre

- dissemination peer review under applicable information quality guidelines. It has not been formally disseminated by EPA. It does not represent and should not be construed to represent any Agency determination or policy. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.

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- Butanol



# CONTENTS

APPENDIX A. OTHER AGENCY AND INTERNATIONAL ASSESSMENTS

.................................................... A-1

A.1. OTHER AGENCY AND INTERNATIONAL ASSESSMENTS

........................................ A-1

APPENDIX B. INFORMATION IN SUPPORT OF HAZARD IDENTIFICATION AND DOSE

RESPONSE AN ALYSIS

......................................................................................................................... B-1

B.1. TOXICOKINETICS

..................................................................................................................... B-1

B.1.1. Absorption

................................................................................................................... B-1

B.1.2. Distribution

................................................................................................................. B-1

B.1.3. Metabolism.................................................................................................................. B-2

B.1.4. Excreti on

...................................................................................................................... B-4

B.1.5. Physiologically Based Pharmacokinetic Models

......................................... B-5

B.2. PBPK MODEL EVALUATION SUMMARY

......................................................................... B-9

B.2.1. Evaluation of Existing tert

- Butanol Submodels

........................................... B-9

B.2.2. Modification of Existing tert

- Butanol Submodels

.................................... B- 11

B.2.3. tert

- Butanol Model Application

....................................................................... B- 14

B.2.4. PBPK Model Code

.................................................................................................. B- 15

B.3. OTHER PERTINENT TOXICITY INFORMATION

........................................................ B- 16

B.3.1. Genotoxicity

............................................................................................................. B- 16

B.3.2. Summary

................................................................................................................... B- 21

APPENDIX C. DOSE

- RESPONSE MODELING FOR THE DERIVATION OF REFERENCE VALUES FOR EFFECTS OTHER THAN CANCER AND THE DERIVATION OF CANCER RISK ESTIMATES

............................................................................................................... C-1

C.1. BENCHMARK DOSE MODELING SUMMARY

................................................................ . C-1

C.1.1. Noncancer Endpoints

............................................................................................. C-1

C.1.2. Cancer Endpoints

................................................................................................... C- 30

APPENDIX D. SUMMARY OF EXTERNAL PEER REVIEW AND PUBLIC COMMENTS AND EPA’S DISPOSITION

............................................................................................................................ D-1

REFERENCES FOR APPENDICES

........................................................................................................................................ 1

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# TABLES

Table A

- 1. Other Agency and International Assessments.

.................................................................................. A-1 Table B

- 1. PBPK model physiologic parameters and partition coefficients.

............................................ B- 12 Table B

- 2. Rate constants for tert

- butanol determined by optimization of the model with experimental data.

.................................................................................................................................. B- 14 Table B

- 3. Summary of genotoxicity (both in vitro and in vivo) studies of tert

- butanol.

................... B- 20 Table C

- 1. Non

- cancer endpoints selected for dose

- response modeling for tert

- butanol

.................... C-2 Table C

- 2. Summary of BMD modeling results for kid ney transitional epithelial hyperplasia in male F344 rats exposed to tert

- butanol in drinking water for 2 years (NTP, 1995) ; BMR = 10% extra risk.

............................................................................................................................................ C-3 Table C

- 3. Summary of BMD modeling results for kidney transitional epithelial hyperplasia in female F344 rats exposed to tert

- butanol in drinking water for 2 years (NTP, 1995); BMR = 10% extra risk.

.............................................................................................................................. C-6 Table C

- 4. Summary of BMD modeling results for relative kidney weights in male F344 rats exposed
to tert

- butanol in drinking water for 15 months (NTP, 1995); BMR = 10% relative deviation and 1 standard deviation.

................................................................................................... C-9 Table C

- 5. Summary of BMD modeling results for relative kidney weights in female F344 rats exposed to tert

- butanol in drinking water for 15 months (NTP, 1995); BMR = 10% relative deviation and 1 standard deviation.

............................................................................... C- 13 Table C

- 6. Summary of BMD modeling results for kidney inflammation in female rats exposed to
tert

- butanol in drinking water for 2 years (NTP, 1995); BMR = 10% extra risk.

......... C- 16 Table C

- 7. Summary of BMD modeling results for thyroid follicular cell hyperplasia in male B6C3F1 mice exposed to tert

- butanol in drinking water for 2 years (NTP, 1995); BMR = 10% extra risk.

.................................................................................................................................................... C- 19 Table C

- 8. Summary of BMD modeling results for thyroid follicular cell hyperplasia in female B6C3F1 mice exposed to tert

- butan ol in drinking water for 2 years (NTP, 1995); BMR = 10% extra risk.

......................................................................................................................................... C- 20 Table C

- 9. Summary of BMD modeling results for absolute ki dney weight in male F344 rats exposed
to tert

- butanol via inhalation for 6 hr/d, 5d/wk for 13 weeks (NTP, 1997); BMR = 10% relative deviation from the mean.

.................................................................................................... C- 23 Table C

- 10. Summary of BMD modeling results for relative kidney weight in male F344 rats exposed
to tert

- butanol via inhalation for 6 hr/d, 5d/wk for 13 weeks ( NTP, 1997); BMR = 10% relative deviation from the mean.

.................................................................................................... C- 26 Table C

- 11. Summary of BMD modeling results for absolute kidney weight in female F344 rats exposed to tert

- butanol via inhalation for 6 hr/d, 5d/wk for 13 weeks (NTP, 1997) ; BMR = 10% relative deviation from the mean.

........................................................................... C- 29 Table C

- 12. Summary of BMD modeling results for relative kidney weight in female F344 rats exposed to tert

- butanol via inhalation for 6 hrs/d, 5d/wk for 13 weeks (NTP, 1997) ; BMR = 10% relative deviation from the mean.

........................................................................... C- 30 Table C

- 13. Cancer endpoints selected for dose

- response modeling for tert

- butanol

........................ C- 31 Table C

- 1 4 . Summary of BMD modeling results for renal tubule adenoma or carcinoma in male F344 rats exposed to tert

- butanol in drinking water for 2 years modeled with adm inistered dose units and including all dose groups (NTP, 1995); BMR = 10% extra risk.

................................................................................................................................................................ C- 32 Table C

- 15. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male F344 rats exposed to tert

- butanol in drinking water for 2 years modeled with administered dose units and excluding high

- dose group (NTP, 1995); BMR = 10% extra risk.

................................................................................................................................................................ C- 34

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- Butanol

Table C

- 16. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male F344 rats exposed to tert

- butanol in drinking water for 2 years modele d with PBPK ( tert

- butanol , mg/L) dose units and including all dose groups (NTP, 1995); BMR = 10% extra risk.

.................................................................................................................................................... C- 36 Table C

- 17. Summar y of BMD modeling results for renal tubule adenoma or carcinoma in male F344 rats exposed to tert

- butanol in drinking water for 2 years modeled with PBPK ( tert

- butanol , mg/L) dose units and excluding high

- dose group (NTP, 1995); BMR = 10% extra risk.

......................................................................................................................................... C- 38 Table C

- 18. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male F344 rats exposed to tert

- butanol in drinking water for 2 years modeled with PBPK (metabolized, mg/hr) dose units and including all dose groups (NTP, 1995); BMR = 10% extra risk.

......................................................................................................................................... C- 40 Table C

- 19. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male F344 rats exposed to tert

- butanol in drinking water for 2 years modeled with PBPK (metabolized, mg/hr) dose units and excluding high

- dose group (N TP, 1995); BMR = 10% extra risk.

......................................................................................................................................... C- 42 Table C

- 20. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male F344 rats exposed to tert

- butanol in drinking water for 2 years modeled with administered dose units and including all dose groups; reanalyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% extra risk.

.................................................................................... C- 44 Table C

- 21. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male F344 rats exposed to tert

- butanol in drinking water for 2 years modeled with administered dose units and excluding high

- dose group; re

- analyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% extra risk.

.................................................................................... C- 44 Table C

- 22. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male F344 rats exposed to tert

- butanol in drinking water for 2 years modeled with PBPK ( tert

- butanol , mg/L) dose units and including all dose groups; reanalyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% extra risk.

............................................................................. C- 47 Table C

- 23. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male F344 rats exposed to tert

- butanol in drinking water for 2 years modeled with PBPK ( tert

- butanol , mg/L) dose units and excluding high

- dose group; reanalyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% extra risk.

........................................................................ C- 47 Table C

- 24. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male F344 rats exposed to tert

- butanol in drinking water for 2 years modeled with PBPK (metabolized, mg/hr) dose units and including all dose groups; reanalyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% extra risk.

........................................................................ C- 49 Table C

- 25. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male F344 rats exposed to tert

- butanol in drinking water for 2 years modeled with PBPK (metabolized, mg/hr) dose units and excluding high

- dose group; reanalyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% extra risk.

........................................................................ C- 49 Table C

- 26. Summary of BMD modeling results for thyroid follicular cell adenomas in female B6C3F1 mice exposed to tert

- butanol in drinking water for 2 years (NTP, 1995); BMR = 10% extra risk.

......................................................................................................................................... C- 52

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- Butanol



# FIGURES

Figure B

- 1. Biotransformation of tert

- butanol in rats and humans.

.............................................................. B-3 Figure B

- 2. Comparison of the tert

- butanol portions of existing MTBE models with tert

- butanol blood concentrations from i.v. exposure by Poet et al. 1997.

.................................................. B-9 Figure B- 3. Schematic of the PBPK submodel for tert

- butanol in rats.

...................................................... B- 11 Figure B

- 4. Comparison of the EPA model predictions with measure d tert

- butanol blood concentrations for i.v., inhalation, and oral gavage exposure to tert

- butanol.

.............. B- 13 Figure B

- 5. Comparison of the EPA model predictions with measured amounts of tert

- butanol in blood after repeated inhalation exposure to tert

- butanol.

.................................................... B- 16 Figure C

- 1. Plot of mean response by dose, with fitted curve for selected model.

................................... C-4 Figure C

- 2. Plot of mean response by dose, wit h fitted curve for selected model.

................................... C-7 Figure C

- 3. Plot of mean response by dose, with fitted curve for selected model (10% relativ e deviation).

.................................................................................................................................................. C- 10 Figure C

- 4. Plot of mean response by dose, with fitted curve for selected model (10% relative deviation).

.................................................................................................................................................. C- 13 Figure C

- 5. Plot of mean response by dose, with fitted curve for selected model.

................................ C- 16 Figure C

- 6. Plot of mean response by dose, with fitted curve for selected model.

................................ C-20 Figure C

- 7. Plot of mean response by dose, with fitted curve for selected model; dose shown in mg/m 3

. ......................................................................................................................................................... C- 24 Figure C

- 8. Plot of mean response by dose, with fitted curve for selected model; dose shown in mg/m 3

. ......................................................................................................................................................... C- 27 Figure C

- 9. Plot of incidence rate by dose, with fitted curve for selected model; dose shown in mg/kg -d.

...................................................................................................................................................... C- 32 Figure C

- 10. Plot of incidence rate by dose, with fitted curve for selected model; dose shown in mg/kg -d.

...................................................................................................................................................... C- 34 Figure C

- 11. Plot of incidence rate by dose, with fitted curve for selected model; dose shown in mg/L.

............................................................................................................................................................ C- 36 Figure C

- 12. Plot of incidence rate by dose, with fitted curve for selected model; dose shown in mg/L.

............................................................................................................................................................ C- 38 Figure C

- 13. Plot of incidence rate by dose, with fitted curve for selected model; dose shown in mg/hr.

.......................................................................................................................................................... C- 40 Figure C

- 14. Plot of incidence rate by dose, with fitted curve for selected mode l; dose shown in mg/hr.

.......................................................................................................................................................... C- 42 Figure C

- 15. Plot of incidence rate by dose, with fitted curve for selected model; dose shown in mg/kg -d.

...................................................................................................................................................... C- 45 Fi gu re C

- 16. Plot of incidence rate by dose, with fitted curve for selected model; dose shown in mg/L.

............................................................................................................................................................ C- 48 Figure C

- 17. Plot of incidence rate by dose, with fitted curve for selected model; dose shown in mg/hr.

.......................................................................................................................................................... C- 50 Figure C

- 18. Plot of mean response by dose, with fitted curve for selected model.

............................. C- 52

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- Butanol



# ABBREVIATIONS

AIC Akaike’s information criterion ARCO ARCO Chemical Company BMD benchmark dose BMDL benchmark dose lower confidence limit BMDS Benchmark Dose Software BMDU benchmark dose upper confidence limit BMR benchmark response BW body weight CA chromosomal aberration CFR Code of Federal Regulations CHO Chinese hamster ovary CYP450 cytochrome P450 DMSO dimethyl sulfoxide DNA deoxyribonucleic acid EDTA e thylenediaminetetraacetic acid EPA U.S. Environmental Protection Agency ETBE ethyl tert

- butyl ether HBA 2- hydroxyisobutyrate HL human leukemia IC 50 half maximal inhibitory concentration i.p. intraperitoneal i.v. intravenous MFO mixed function oxidase MPD 2- methyl -1,2- propanediol MTBE methyl tert

- butyl ether NADPH nicotinamid e adenine dinucleotide phosphate NTP National Toxicology Program OH hydroxyl radical PBPK physiologically based pharmacokinetic POD point of departure SD standard deviation SE s tandard error TWA time

- weighted average

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# APPENDIX A. O THER AGENCY AND 1

2

3

4 

# INTERNATIONAL ASSESSMENTS

A.1. OTHER AGENCY AND INTERNATIONAL ASSESSMENTS

**Table A-1.**  **Other Agency and International**  **Assessments**

**.**

Organization Toxicity value

American Conference of Governmental Industrial Hygienists ( ACGIH, 2012 ) Threshold Limit Value

– 100 ppm (303.1493 mg/m 3 ) time

- weighted average (TWA) for an 8

- hour workday and a 40

- hour work week

National Institute of Occupational Safety and Health ( NIOSH, 2007 ) Recommended Exposure Limit

– 100 ppm (300 mg/m 3 ) TWA for up to a 10

- hour workday and a 40

- hour work week

Occupational Safety and Health ( OSHA, 2006 ) Permissible Exposure Limit for general industry

– 100 ppm (300 mg/m 3 ) TWA for an 8

- hour workday
Food and Drug Administration ( FDA, 2011a
, b ) tert

- Butyl alcohol: Indirect food additive that may be safely used in surface lubricants employed in the manufacture of metallic articles that contact food, subject to the provisions of this section (21 C ode of F ederal R egulations [CFR] 178.3910); substance may be used as a defoaming agent (21 CFR 176.200).

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# APPENDIX B. INFORMATION IN SUPPORT OF 1

2

3

4

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7
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11
12
13
14 15

16

17
18 19
20
21
22
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24
25
26
27
28

29

30
31
32
33 

# HAZARD IDENTIFICATION AND DOSE

- RESPONSE ANALYSIS

B.1. TOXICOKINETICS

There is little information on the absorption, distribution, metabolism, or excretion of tert

butyl alcohol ( t e rt

- bu tanol ) in humans . T he studies identified were conducted in conjunction with methyl tert

- bu t yl ether ( MTBE ) and ethyl tert

- butyl ether ( ETBE ) because t ert

- butanol is a primary
metabolite o f these two compounds

. Several studies examining some aspect of the toxicokinetic
behavior of t e rt

- bu tanol in animals have been identified. Many of the studies were carried out in conjunction with other specific end p o ints (e.g., developmental). ARCO (1983) determined that
there were no d ifferences in the pharmacokinetics of t ert

- butanol following either oral (i.e., gavage) or inhalation exposure. A l though there is some information available after both oral and inhalation

exposure s , many studies also administered t e rt

- butanol via intrap erit oneal (i.p.) or intravenous (i.v.) injection. A l though these studies do not inform the absorption of t ert

- butanol , they can provide information o n d istribution, metabolism, and excretion.



### B.1.1. A bsorption

Extensive t ert

- butanol toxicity testing data submitte d by industry to the U.S. Environmental Protection Agency ( E PA ) under Section 8(e) of the Toxic Substances Control Act and other reporting requirements indicate that t e rt

- bu tanol is rapidly absorbed after oral administration. Very little of the administered dose was excreted in the feces of rats

, i n dicating 99% of the compound was absorbed. C o m parable blood levels of t ert

- butanol and its metabolites have been
observed af ter acute or al ( 350 mg/kg ) and inhalation (6,164 mg/m 3 for 6 hours ) exposures ( ARCO,
1983 ) ; however

, the absorption rate after inhalation exposure could not be determine d because the blood was saturated with radioactivity aft er 6 ho urs of a 6,164

- mg/m 3 exposure. Based on b lood concentrations, a b sorption was found to be complete at 1.5 hours following repeated oral exposure

, with an apparent zero

- o r der decline in t ert

- butanol concentration for the majority of the elimination phase

, t h us indicating that previous exposures did not affect the absorption of t ert

butanol ( Faulkner et al., 1989 ).



### B.1.2. D istribution The available animal data suggest that t ert

- butanol is distributed throughout the body following oral , i n halation , and injection exposures ( Poet et al., 1997 ; Faulkner et al., 1989 ; ARCO,
1983 ). Nihlén et al. (1995) determined a partition coefficient for t ert

- butanol using blood from
human volunteers. T h e study was approved by an ethical review board

, and informed consent was

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obtained from the participants. Their results indicated that t ert

- butanol would rapidly move from 

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38 the blood into the tissues.

t e rt -B utanol was found in the kidney, liver, and blood of both sexes of rat following oral

exposure , bu t ma le rat s retain ed more t ert

- butanol compared with females ( Williams and Borghoff,
2001 ). Radioactivity was found in the low

- molecular

- weight protein fraction from the kidney cytosol in male rats but not female rats

, in d icating that t ert

- butanol or one of its metabolites was bound to α 2u - globulin. Further analysis determined that it was t ert

- butanol that was bound and not
its metabolite acetone. T h e majority of t ert

- butanol in the kidney cytosol was eluted as the free compound in both males and females, but a small amount was also found associated with the high

molecular

- w ei ght protein fraction in both males and females. Borghoff et al. (2001) found similar results in rats after inhalation exposure

. M ale r at kidney

- to

- blood ratios were significantly elevated over female ratios at all dose levels and exposure durations. A l though t he female t ert

- butanol kidney

- to

- b lood ratio remained similar with both duration and concentration, the male t e rt

- butanol kidney

- to

- b lood ratio increased with duration. T he liver

- to

- blood ratios were similar regardless of exposure duration, concentration, o r sex

. Both of these studies indicate distribution to the liver and kidney with kidney retention of t e rt

- b utanol in the male rat.



### B.1.3. Me tabolism A general metabolic scheme for t ert

- butanol , illustrating the biotransformation in rats and humans, is shown in F i gure B–1 below. Urinary metabolites of t ert

- butanol in a human male
volunteer s w h o ingested a gelatin capsule containing 5 mg/kg [ 13 C]

- t ert

- butanol were reported to
be 2

- me thyl

- 1 ,2 -propanediol (MPD) and 2

- hydroxyisobutyrate ( Bernauer et al., 1998 ). Minor metabolites of unconjugated t e rt

- bu tanol

, t ert

- butanol glucuronides

, and trace s of the sulfate conjugate a lso w ere detected. The study was approved by an ethical review board; however, no information regarding informed consent was reported. I n the same study, 2- hydroxyisobutyrate, MPD, a nd t e rt

- butanol sulfate were identified as maj or metabolites in rats

, while acetone, t ert

butanol , an d t e rt

- butanol glucuronides were identified as minor metabolites ( Bernauer et al., 1998 ). Baker et al. (1982) found that t ert

- butanol was a source of acetone, but also may have stimulated

a c etone production from other sources.
T here are no studies that id e ntify specific enzymes responsible for the biotransformation of

t e rt

- b utanol . U sing purified enzyme s from Sprague

- Dawley rats or whole

- liver cytosol from Wistar
rats, a lcohol dehydrogenase had n egligible or no activity toward t ert

- butanol ( Videla et al., 1982 ; Arslanian et al., 1971 ). Other in vitro studies have implicated the liver microsomal mixed function
oxidase ( MFO) system, namely cytochrome P

- 4 50 (CYP450) ( Cederbaum et al., 1983 ; Cederbaum and Cohen, 1980 ). In the first study, incubation of t ert

- butanol at 35 mM with Sprague

- Dawley rat
liver microsomes a nd a nicotinamide adenine dinucleotide phosphate - ( NADPH ) generating system
resulted in the p r oduction of formaldehyde at a concentration of approximately 25 nmoles/mg protein / 30 min

. A ccording to study authors, the amount of formaldehyde generated by tert

- butanol

is a pprox i mately 30% of the amount of formaldehyde formed during the metabolism of 10 mM

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aminopyrene in a similar microsomal system. The rate of formaldehyde generation from 

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22 t ert

- butanol was increased to about 90 nmol/mg protein /30 min upon addition of azide, which
inhibits catalase and thereby prevent s the decomposition of hydrogen peroxide (H 2 O 2 ). In other experiments within the same study, there was a major reduction of formaldehyde formation when
H 2 O 2 was included but NADPH was absent or when the microsomes were boiled prior to incubation. Additionally, the rate of formaldehyde formation in the microsomal oxidizing system was found to be dependent on the concentration of t ert

- butanol

, with apparent K m and V max values of 30 mM and
5.5 nmol/min/mg protein , respecti vely

. The study authors concluded that t ert

- butanol is metabolized to formaldehyde by a mechanism involving oxidation of NADPH, microsomal electron flow, and the generation of hydroxyl

- radical (

· OH) from H 2 O 2 , possibly by a Fenton

- type or a Haber

Weiss iro n- catalyzed reaction involving CYP450

, which might serve as the iron chelate ( Cederbaum and Cohen, 1980 ).

CH 3 OH CH 3 CH 3 CYP450

CH 3 CH

3 OH O [O] CH 3 CH 3 OH OOH

CH

3
CH 3 OH

OH

CH 3 CH 3 O t-butanol 2-methyl-1,2-propanediol

acetone 2-hydroxyisobutyric acid

O O

O S

CH 3 CH 3

O CH 3

t-butyl sulfate t-butyl glucuronide CH 3

CH 3 CH 3 glucuronide –O

rats, humans

rats rats, humans CH 2 O formaldehyde

**Figure B-1.**  **Biotransformation of** t ert

**- butanol**  **in rats and humans.**

Source: NSF International ( 2003 ) , AT SDR ( 1996 ) , Bernauer et al. ( 1998 ) , Amberg et al. ( 1999 ) , and Cederbaum and Cohen ( 1980 ).

In a follow

- up s tudy, t ert

- butanol was oxidized to formaldehyde and acetone by a variety of systems known to generate ·OH radical, including rat liver microsomes or other nonmicrosomal

. OH generating systems ( Cederbaum et al., 1983 ) . The nonmicrosomal tests included two chemical systems: (1) the iron

- ca t alyzed oxidation of ascorbic acid (ascorbate

- Fe

- EDTA

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[e thylenediaminetetraacetic acid ]) and (2) the Fenton system of chelated ferrous iron and H 2 O 2. In 

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38 both of these Fenton

- type systems, H 2 O 2 served as a precursor of ·OH. Additionally, a Haber

- Weiss enzymatic system involving oxidation of xanthine by xanthine oxidase in the presence of Fe

- EDT A was used. In this system, ·OH is thought to be produced by the interaction of H 2 O 2 and superoxide (O 2 · - ). Further experiments demonstrated the involvement of ·OH in either the ascorbate

- Fe

- EDTA or the xanthine oxidation systems based on inhibition of for maldehyde and acetone production
from t ert

- butanol upon addition of ·OH

- scavenging agents (e.g., benzoate, mannitol). Some of the experiments in this study of the oxidation of t ert

- butanol by the liver microsomal metabolizing system were similar to those i n the previous study except that, in addition to formaldehyde, acetone formation was also measured. Again, these experiments showed the dependence of the microsomal metabolizing system on an NADPH

- generating system and the ability of H 2 O 2 to enhance, but n ot replace, the NADPH

- generating system. Addition of chelated iron (Fe

- EDTA) boosted the microsomal production of formaldehyde and acetone, while ·OH scavenging agents inhibited their production. The study authors noted that neither Fe

- EDTA nor ·OH scaveng ing agents is known to affect the CYP450 catalyzed oxidation of typical MFO substrates such as aminopyrene or aniline. The study also showed that known CYP450 inhibitors, such as metyrapone
or SKF

- 525A, inhibited the production of formaldehyde from aminopy rene but not from t ert

butanol . Finally, typical inducers of CYP450 and its MFO metabolizing activities, such as phenobarbital or 3

- methylcholanthrene, had no effect on the extent of microsomal metabolism of

t ert

- butanol to formaldehyde and acetone. Accord ing to the study authors, the oxidation of t ert

butanol appears to be mediated by ·OH (possibly via H 2 O 2 ), which can be produced by any of the tested systems by a Fenton

- type reaction as follows:

H 2 O 2 + Fe 2+ - chelate → ·OH + OH

- + Fe 3+ - chelate

According t o this reaction, reduction of ferric iron (Fe 3+ ) to ferrous iron (Fe 2+ ) is required for continuous activity. The study authors concluded that the nature of the iron and the pathway of
iron reduction within the microsomes remain to be elucidated even thou g h an NADPH

- dependent
electron transfer or O 2 · - might be involved ( Cederbaum et al., 1983 ).



### B.1.4. Ex cretion

Hu man data on the excretion of t ert

- butanol comes from studies of MTBE and ETBE ( Nihlén et al., 1998a

, b ) . Eight or ten male human volunteers were exposed to 5, 25, or 50 ppm MTBE or ETBE b y inhalation during 2 hours of light exercise. The half

- l ife of t ert

- butanol in urine following MTBE exposure w as 8.1 ± 2.0 hours (average of the 25 - and 50

- ppm MTBE doses); the half

- life of

t e rt

- b utanol in urine following ETBE exposure w as 7.9 ± 2.7 hours (average of 25 - and 50

- ppm ETBE doses). The renal clearance rate of t e rt

- bu tanol was 0.67 ± 0.11 mL/hr

- kg with MTBE

exposure ( average of 25

- and 50

- ppm MTBE doses); the renal clearance rate was 0.80 ± 0.34 mL/hr

- k g w ith ETBE exposure (average of 25 - and 50

- ppm ETBE doses).

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Amberg et al. (2000) exposed six volunteers (three males and three females, 28 ± 2 years 

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38 old) to 18.8 and 170 mg/m 3 ETBE. Each exposure lasted 4 hours, and the two concentrations were
administered to the same volunteers 4 weeks apart. Urine was collected at 6

- hour intervals for
72 hours following exposure

. tert

- Butanol and two metabolites of tert

- butanol

, 2- hydroxyisobutyrate (H BA ) and MPD

, also were identified in urine. At an ETBE level of 170 mg/m 3
, t ert

- butanol displayed a half- life of 9.8 ± 1.4 hours. At the low

- exposure ETBE concentration, the t ert

- butanol half- life was 8.2 ± 2.2 hours. The predominant urinary metabolite identified was HBA, excreted in urine at 5

– 10 times the amount of MPD and 12

– 18 times the
amount of t ert

- butanol (note: urine samples had been treated with acid before analysis to cleave

con jugates). HBA in urine showed a broad maximum at 12

– 30 hours after exposure to both concentrations, with a slow decline thereafter. MPD in urine peaked at 12 and 18 hours after exposure to 170 and 18.8 mg/m 3 ETBE, respectively, while t ert

- butanol peaked at 6 hours after
both concentrations. Amberg et al. (2000) exposed F344 NH rats to 18.8 and 170 mg/m 3 ETBE. Urine was
collected for 72 h our s following exposure. Similar to humans, rats excreted mostly HBA in urine, followed by MPD and tert

- bu t anol

. The half

- life for t ert

- butanol in rat urine was 4.6 ± 1.4 hours at
ETBE levels of 170 mg/m 3
, but half- life could not be calculated at the ETBE concentration of
18.8 m g/m 3

. Corresponding half

- lives were 2.6 ± 0.5 and 4.0 ± 0.9 hours for MPD and 3.0 ± 1.0 and
4.7 ± 2 .6 hours for HBA. In Sprague

- Dawley rats treated with radiolabeled t ert

- butanol by gavage at 1, 30, or 5 00 mg/kg, a fairly constant fraction of the administered radioactivity (23

– 33%) was recovered in the urine at 24 hours postdosing. H o wever, only 9% of a 1500

- mg/kg administered dose was recovered in urine, suggesting that the urina ry route of elimination is saturated following
this dose ( ARCO, 1983 ).



### B.1.5. P hysiologically B ased P harmacokinetic M odels

There have been no physiologically bas ed pharmacokinetic ( PBPK ) models developed specifically for administration of t e rt

- b utanol

. The majority studied t ert

- butanol as the primary metabolite after oral or inhalation exposure to MTBE or ETBE. T h e most recent models for MTBE oral and inhalation exposure include a component for the binding of t e rt

- b utanol to α 2u - globulin ( Borghoff et al., 2010 ; Leavens and Borghoff, 2009 ). Faulkner and Hussain (1989) used a one

- compartment open model with Michaelis

- Menten
elimination kinetics to fit t e rt

- b utanol blood concentrations obtained from C57BL/6J mice given i.p. injections of 5, 10, or 2 0 mmol/kg t ert

- butanol

. Elimination was indistinguishable from first -order kinetics in the range of concentrations studied. A n i ncrease in V max and decrease in apparent volume of distribution with dose are consistent with this model and suggest the exist en c e of parallel elimination processes. Borghoff et al. (1996) developed a PBPK model for MTBE and its metabolite t ert

- butanol in

rats. D oses a nd blood levels were taken from several published studies. The initial model included a

tissue

- sp ecific five

- c ompartment model using blood, liver, kidney, muscle

, and fat with liver

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metab olism rate constants. The model was able to predict the accumulation of t ert

- butanol in blood, 

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38 but not its clearance. A two

- compartment model was better at predicting t ert

- butanol blood levels,
however

, the volume of the total body water had to be changed to obtain an adequate fit, suggesting
dose- dependent changes in the kinetics of t ert

- butanol

. Overall, evaluation of the t ert

- butanol models suggests that the clearance of t ert

- butanol from the blood of rats after exposure to MTBE involves processes beyond metabolic elimination. Nihlén and Johanson (1999) developed a PBPK model for evaluation of inhalation exposure
in hum an s to the gasoline additive ETBE

. Model compartments for ETBE included lungs ( with arterial blood), liver, fat, rapidly perfused tissues, resting muscles, and working muscles. T h e same set of compartments and an additional urinary excretion compartment we re used for the
metabolite

, t e rt

- b utanol

. First

- order metabolism was assumed in the model, and tissue/blood partition coefficients were determined by in vitro methods ( Nihlén et al., 1995 ). Estimates of individual metabolite parameters of eight subjects were obtained by fitting the PBPK model to experimental data from humans (5, 25, or 5 0 ppm ETBE ; 2- hour exposure) ( Nihlén et al., 1998a ). This model was applied primarily t o predict levels of the biomarkers ETBE and t ert

- butanol in blood, urine, and exhaled air after various scenarios, such as prolonged exposure, fluctuating exposure, and exposure during physical a ctivity ( Nihlén and Johanson, 1999 ). Rao and Ginsberg (1997) developed a PBPK model for MTBE and its principal metabolite,

t e rt

- b utanol , based on the Borghoff et al. (1996) model. The modified model included a skin compartment to simulate dermal absorption of MTBE during bathing or showering. A br ain compartment was added as a target organ for M T BE

- induced neurological responses. MTBE
metabolism to t e rt

- b utanol was assumed to occur in the liver through two saturable pathways. The

t e rt

- b utanol portion of the model included further metabolism of t ert

- butanol in the liver, exhalation in the lungs, and renal excretion (in the human model only). T h e model was validated against published human and rat data and was u s ed to help determine the contribution of t ert

butanol in the acute central nervous system effects seen after MTBE dosing.
The Rao and Ginsberg (1997) model used peak concentrations of MTBE and t ert

- butanol in
the b lood and brain for interspecies, route

- to

- r oute, and low/high

- dose extrapolations. The MTBE/ t e rt

- bu tanol PBPK model was adapted to humans by adjusting physiology according to literature values, incorporating the blood/air partition coefficient for humans r e ported by Johanson et al. (1995)

, and allometrically scaling the metabolic rate based on body weight. A renal elimination component was added to account for the small percent a ge of MTBE disposition that occurs in humans via urinary excretion of t e rt

- bu tanol

. t ert -B utanol concentrations in human blood during and after MTBE exposure (25 or 50 ppm fo r 2 hours ) were accurately predicted by the
human model ( Johanson et al., 1995 ). Kim et al. (2007) expanded the Borghoff et al. (1996) model to develop a multi

- exposure route model for MTBE and its primary metabolite, t e rt

- bu tanol , i n humans. The significant features and advantages of the Kim et al. (2007) model are that parameters used for quantif ying the

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pharmacokinetic behavior of MTBE and t ert

- butanol are calibrated using time

- series 

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38 measurements from controlled

- exposure experiments in humans as reported by Prah et al. ( 2004 ). MTBE partition coefficient values d e scribed in the Licata et al. (2001) model and skin compartment parameters from the Rao and Ginsberg (1997) model were incorporated. The PBPK model for MTBE consists of nine primary compartments representing the lungs, skin, fat, kidney, stomach, intestine, liver, r a p idly perfused tissue, and slowly perfused tissue. The t ert

- butanol model consists of three compartments representing blood, liver, and other tissue. Leavens and Borghoff (2009) developed a PBPK model for inhalation exposures in male and female rats that expanded on Borghoff et al. (1996) and Rao and Ginsberg (1997) to include the sex

specific e ffects o f MTBE binding to α 2u - globulin, a protein unique to male rats, and to describe the
induction of t e rt

- b utanol metabolism after repeated exposures. Although t he primary purpose of
the model was to estimate MTBE and t e rt

- bu tanol tissue concentrations after MTBE exposure, the model was also parameterized to include inhalation uptake of t e rt

- bu tanol . T he t ert

- butanol portion of the model was calibrated using data from rat exposures to t e rt

- bu tanol as well as MTBE. Model compartments included blood, brain, fat, gastrointestinal tissues, kidney, liver, poorly p e rfused tissues (blood flow of <100 m L / m in/100 g of tissue: bone, muscle, skin, fat), and rapidly perfused
tissues

. Distribution of MTBE and t e rt

- b utanol was assumed to be perfusion (i.e., blood

- flow)
limited. Th is model used the same a ssumptions as Borghoff et al. (1996) regarding MTBE metabolism and kinetics, and assumed that t e rt

- bu tanol was metabolized only in the liver through
one low

- aff inity pathway and excreted through urine

. Th e model described binding of MTBE or

t e rt

- b utanol with α 2u - globulin in the kidney, due to the high concentration of α 2u - globulin in the kidney. As chemicals bind to α 2u - globulin, the rate of hydrolysis of the protein decreases and causes
accumulation i n t h e kidney ; however, there is no evidence that binding of α 2u - globulin affects its synthesis, secretion, or circulating concentrations [ Borghoff et al. (1990) as cited in Leavens and Borghoff (2009) ]. Equations describing this phenomenon were included in the model for male rats only t o account for the effects of the binding with α 2u - globulin on metabolism of MTBE and t ert

buta nol

. Partition coefficient values in the model that differed from those published in previous PBPK models included poorly perfused tissues:blood and kidney:blood values. T h e kidney:blood value was based on calculated kidney : b l ood concentrations in female rats only because of the lack
of α 2u - globulin

- associated effects in female rats. The deposition of t ert

- butanol during inhalation in the nasal cavity and upper airways was reflected in the high blood : a i r partition coefficient for t ert

butanol , an d the abil ity of t e rt

- butanol to induce its own metabolism after chronic exposure was also t aken into account. N o differences in the induction of metabolism were reported between
males and females. T h e model simulated concentrations of MTBE and t ert

- butanol in the brain, liver, and kidney of male and female rats following inhalation exposure at concentrations o f 1 00, 400, 1,750, or 3,000 ppm MTBE, and compared them to m e asured concentrations of MTBE and t ert

butanol fr om rats exposed at those levels.

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Concent rations of MTBE and t ert

- butanol in the brain and liver were similar in male and 

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37 female rats during exposure and postexposure, but the concentrations of the chemicals in the kidney were significantly different in male rats when compared with female rats. T he additional
parameter accounting for α 2u - globulin protein

- binding in this PBPK model more accurately reflects
the metabolism of both MTBE and t ert

- butanol in male rat kidneys over time compared with other
PBPK models

. The model highlights that binding ca n stimulate increased renal effects in male rats after exposure to MTBE and t ert

- butanol

. The assumptions made to reflect t ert

- butanol metabolism induction and deposition in the nasal cavity and upper airways generally were supported by measured data from rats exposed to 250, 450, or 1,750 ppm t ert

- butanol as evidenced by the fact
that the model was within one standard deviation of the mean concentrations for most data points. However, the model overpredicted the concent ration of t ert

- butanol in the brain, liver, and kidney of male rats after repeated exposures

. Borghoff et al. (2010) modified the PBPK model of Leavens and Borghoff (2009) by adding

or al g avage and drinking water exposure components. T his was done to compare different dose metrics to the toxicity observed across different studies. Th e Borghoff et al. (2010) model assumed
first

- o rder uptake of MTBE absorption from the gut, with 100% of the MTBE d ose absorbed for both drinking water and oral gavage exposures. Th e y conducted a series of pharmacokinetic studies comparing the effects of different rat strains and different dosing vehicles on the blood

concentration

- t i me profiles of MTBE and t ert

- butanol following MTBE exposure. The effects of exposure to MTBE via drinking water, oral gavage, and inhalation routes over 7 and 91 d a ys on male and female rats were modeled and compared w i th measured data collected from F344 rats (exposed 28 days) and Wistar Han rats (exposed 14 and 93 days). The model predicted the blood concentrations of t er t

- bu tanol that were observed after 250 or 1,000 mg/kg

- d ay administration of MTBE in males and female s , as well as the blood concentrations of MTBE after 1,000 mg/kg

- d ay , but was not able to predict peak co ncentrations of MTBE after 250 mg/kg

- d a y in males or females using either olive oil or 2% Emulphor as vehicles. When comparing strains, the blood concentrations were similar across strain and sex , ex cept in female Sprague

- Daw ley rats administered 1, 000 mg/ kg

- day MTBE. The female Sprague

- Dawley rats had a significantly ( p

- v a lue not specified) higher blood concentration of both MTBE and t ert

butanol c ompared w ith the F344 and the Wistar Han females. However, the study authors
considered this an outlier and st i ll considered the metabolic patterns similar. The model overpredicted the amount of MTBE in the male rat kidney, but it a c curately predicted the level of

t e rt

- b utanol in the male rat kidney at all exposures tested. The model did not accurately predict the kidney concentrations of t e rt

- bu tanol in the female kidney after exposure to MTBE via drinking water, but the study authors attributed the inaccuracies t o the study design as opposed to the
model formulation. A l l of the t ert

- butanol entering the submodel comes from MTBE metabolism in
the liver

, an d the model does not include a separate oral intake of t ert

- butanol

.

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## B.2. PBPK MODEL EVALUATION SUMMARY 1

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26 B.2.1. Evaluation of Existing tert

- Buta nol S ubmodels

The Blancato et al. (2007) and Leavens and Borghoff (2009) PBPK model s for MTBE were evaluated by comparing predictions from the t ert

- b ut anol portions of the models with the

t ert

- b utanol i.v. data of Poet et al. (1997) ( see Figure B-2 ). Neither model adequately represented
the t ert

- bu tanol b lood concentrations. Modifications of model assumptions for alveolar ventilation, explicit pulmonary compartments

, a nd induction of metabolism of tert

- butanol did not significantly improve model fits to the data. Attempts to r eo p timiz e model parameters in the tert

- butanol
submodels of Blancato et al. (2007) and Leavens and Borghoff (2009) to match blood concentrations from the i.v. dosing study were un su ccessful

.

A) B)

**Fig ure**  **B-2. C**  **om parison of the**  tert

**- butanol**  **portions of existing MTBE models with**
tert

**- butanol**  **blood con centratio**  **ns from i .v.**  **exposure by Poet et al. 1997**

**.**
Neither the a) Blancato et al. (2007) nor the b) Leavens and Borghoff (2009) model adequately represents the measured ter t

- b utanol blood concentrations.

The PBPK s ub m odel for t ert

- butanol in rats was developed in acslX (Advanced Continuous Simulation Language, Aegis, Inc., Huntsville, Alabama) by adapting information from the many
PBPK models that were developed in rats and humans for the structurally related substance, MTBE

, and it s m etab o lite tert

- butanol ( Borghoff et al., 2010 ; Leavens and Borghoff, 2009 ; Blancato et al.,
2007 ; Kim et al., 2007 ; Rao and Ginsberg, 1997 ; Borghoff et al., 1996 ). A brief description

com paring the Blancato et al. (2007) and ( Leavens and Borghoff, 2009 ) models is given

, followed by an evaluation of the MTBE models and the assumptions adopted from MTBE models or mod if ied in
the tert

- bu tanol m odel.

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The Blancato et al. (2007) model is an update of the earlier Rao and Ginsberg (1997) model

, 

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38 and the Leavens and Borghoff (2009) model is an update of the Borghoff et al. (1996) model. Both
the Blancato et al. (2007) and Leavens and Borghoff (2009) models are flow

- limited models that predict amounts and concentrations of MTBE and its metabolite t e rt

- bu tanol in blood and six tissue compartments: liver, kidney, fat, brain

, a nd rapidly and slowly perfused tissues. These tissue compartments are linked through blood flow, following an anatomically accurate, typical, physiologically b a sed description ( Andersen, 1991 ) . The parent ( M TBE) and metabolite ( t e rt

- b utanol ) models are interlinked by the metabolism of MTBE to t ert

- butanol in the liver. Routes of exposure included in the models are oral and inhalation for MTBE ; Leavens and Borghoff (2009) included inhalation exposure to t e rt

- bu tanol . Oral doses are assumed to be 100% bioavailable and 100% absorbed from the gastrointestinal tract represented with a first

- o r der rate constant. Following inhalation of MTBE or t e rt

- b utanol , the chemical is assumed to directly enter the systemic blood supply

, a nd the respiratory tract is assumed to be at a pseudo

- steady state.
Metabolism of MTBE by CY P 4 50s to formaldehyde and t ert

- butanol in the liver is described with
two Michaelis

- M en ten equations representing high - and low

- affinity enzymes. t ert -B utanol is either conjugated with glucuronide or sulfate or further metabolized to acetone through MPD a nd HBA ; both of these processes are described by a single Michaelis

- M en ten equation in the models. All of
these m o del assumptions are valid for t e rt

- butanol an d were applied to the EPA -developed t ert

butanol PB PK model

, except for the separate brain compartment. T he brain compartment was lumped with other richly perfused tissues in the EPA t e rt

- bu tanol PBPK model. In addition to differences in parameter values b etween the Blancato et al. (2007) and the
Leavens and B orghoff (2009) models , there were three difference s in the model structure: (1) the alveolar ventilation was reduced during exposure, (2) the rate of tert

- b ut anol metabolism increased over time due to induction of CYP enzymes

, a nd (3) binding of MTBE an d tert

- butanol to

α 2u -globulin was simulated in the kidney of male rats. The Blancato et al. (2007) model was configured through EPA’s PBPK modeling framework, ERDEM (Exposure

- R ela ted Dose Estimating Model), w hich includes explicit pulmonary c ompartments. The modeling assumptions related to alveolar ventilation, explicit pulmonary compartments

, a nd indu ction of metabolism of tert

- butanol
are discussed in the model evaluation section.
MTBE and t e rt

- b utanol binding to α 2u -globulin in the kidneys of male rats were incorporated in the PBPK model of MTBE by Leavens and Borghoff (2009) . Binding to α 2u -globulin is one hypothesized MOA for the observed kidney effects in MTBE

- ex p osed animals. For a detailed description of t he role of α 2u -globulin and other MOAs in kidney effects

, see the kidney MOA sect ion of this document (see Section 1.1.1 )

. Binding of MTBE to α 2u - globulin was applied to sex differences in kidney concentrations of MTBE and t e rt

- b utanol in the Leavens and Borghoff (2009) model

, but acceptable estimates of MTBE and t e rt

- bu tanol pharmacokinetics in the blood are predicted in
other models that did not consider α 2u - globulin binding. Given the uncertainty of t ert

- butanol binding to α 2u - globulin

, it was not included in the t ert

- butanol PBPK sub model.

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B.2.2. Modification of Existing tert -B utanol S ubmodels 1

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13

14 15

16 17 18 19 To account for the t ert

- butanol blood concentrations after i.v. t ert

- butanol exposure, the model was modified by adding a pathway for reversible sequestration of t e rt

- bu tanol in the blood. This could represent binding of t e rt

- b utanol to proteins in blood ( see Figure B-3 ) . The JPEC PK
studies show ed t h at approximately 60% of the radiolabel in whole blood is in the plasma

, providing
some limited evidence for association of t e rt

- b utanol with components in blood. The PBPK model represented the rate of change in the amount of t e rt

- bu tanol in the sequestered blood compartment (A blood2 ) with the following equation where K ON is t he binding rate constant, CV is the free t ert

butanol c oncentration in blood, K OFF is the unbinding rate constant

, and C blood2 is the concentration
of t e rt

- b utanol bound in blood (equal to A blood2 /V blood ).

dA blood2 /dt = K ON *CV* - K OFF *C blood2

**Figure B-3**  **. Schematic of the PBPK sub model for**  tert

**- butanol**  **in rats.**

Exposure can be via multiple routes including inhalation, oral

, or i.v. dosing. Metabolism of tert

butanol oc curs in the liver and is described by M ichaelis

- Menten equations with one pathway for
tert

- b utanol

. t ert -B utanol is cleared via exhalation and tert

- butanol is additional ly cleared via urinary excretion. See Table B

- 1 for definitions of parameter abbreviations.

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**Table B-1**  **. PBPK model physiologic parameters and partition coefficients**

**.** 

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12 Body weight and organ volumes as fraction of body weight Body Weight (kg) 0.25 ( Brown et al., 1977 ) Body fraction that is blood perfused (Fperf) 0.8995 ( Brown et al., 1977 )

Liver 0.034 ( Brown et al., 1977 ) Kidney 0.007 ( Brown et al., 1977 )

Fat 0.07 ( Brown et al., 1977 ) Rapidly perfused 0.04 ( Brown et al., 1977 ) Slowly perfused 0.7485 a

Blood 0.074 ( Brown et al., 1977 ) Cardiac output and organ blood flows as fraction of cardiac output Cardiac output (L/hr) 5.38 ( Brown et al., 1977 ) b Alveolar ventilation (L/hr) 5.38 ( Brown et al., 1977 ) c

Liver 0.174 ( Brown et al., 1977 ) d
Kidney 0.141 ( Brown et al., 1977 )

Fat 0.07 ( Brown et al., 1977 ) Rapidly perfused 0.279 e Slowly perfused 0.336 ( Brown et al., 1977 )
Partition coefficients for tert

- butanol
Blood:air 481 ( Borghoff et al., 1996 )
Liver:blood 0.83 ( Borghoff et al., 1996 )
Fat:blood 0.4 ( Borghoff et al., 1996 ) Rapidly perfused:blood 0.83 ( Borghoff et al., 1996 ) Slowly perfused:blood 1.0 ( Borghoff et al., 1996 ) Kidney:blo od 0.83 ( Borghoff et al., 1996 )

a Fperf

− Σ(other compa rtments)
b 15.2*BW 0.75 (bw = body weight)

c Alveolar ventilation is set equal to cardiac output
d S um of liver and gastrointestinal blood flows

e 1

− Σ(all other compartments)

.

T he physiologic parameter values obtained from the literature are shown in Table B-1 ( Brown et al., 1977 )

. t ert -B utanol partition coefficients were obtained from literature in which they were determined by the ratios of measured tissue:air and blood:air partition coefficients ( Borghoff et al., 1996 )

. The parameters describing rate constants of metabolism and elim ination of

tert

- b utanol w er e obtained from the literature ( Blancato et al., 2007 ) and kept fixed because these have been optimized to tert

- bu t anol blood concentrations measured after MTBE exposure , which is
also metabolized to t e rt

- b utanol . The parameters describing t ert

- butanol absorption and

t e rt

- b utanol sequestration in blood were estimated by optimizing the model to the blood t ert

butanol t ime

- c ourse data for rats exposed via i.v., inhalation , a nd oral routes ( Leavens and Borghoff,
2009 ; Poet et al., 1997 ; ARCO, 1983 ) . The model parameters were estimated with the acslX

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optimization routine to minimize the log

- likelihood function of estimated and measured 

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17 18 19

20 21 t ert

- butanol concentrations. The Nedler

- Mead algorithm was used with heteroscedasticity allowed to vary between 0 and 2. The predictions of the model with optimized parameters have a much improved fit to the t ert

- butanol blood concentrations after t ert

- butanol i.v.
, as shown in panel A of Figure B -4 . Additionally

, the model adequately estimate d the t ert

- butanol blood concentrations after inhalation and oral gavage exposures. The optimized parameter values are shown in Table
B-2 . The ARCO (1983) study mea sured t ert

- butanol in plasma only, unlike the Poet et al. (1997) and Leavens and Borghoff (2009) studies that measured tert

- butanol in whole blood . Based on the measurements of plasma and who l e blood by JPEC 2008
, the concentration of t ert

- butanol in plasma is approximately 60% of the concentration in whole blood. The t e rt

- butanol plasma concentrations measured by ARCO were increased (divided by 60%) to the expected concentration
in whole bloo d for comparison with the PBPK model.

A) B)

C)

**Figure B-4**  **. Comparison of the EPA model predictions with measured**  tert

**- butanol**  **blood concentrations for i.v., inhalation ,**  **and oral gavage exposure to** tert

**- butanol** 

**.**
A) i .v. data from Poet et al. (1997) ; B) inhalation data from Leavens and Borghoff (2009) ; and C) oral gavage data from ARCO (1983) with the optimized parameter values as shown in Table B-2

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**Table B-2**  **. Rate constants for**  tert

**- butanol**  **determined by optimization of the**  

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**.**

Parameter Value Source or Reference Metabolism (VM TBA ; mg/kg

- hr) a 8.0 Blancato et al. (2007)
Metabolism (KM TBA ; mg/L) 28.8 Blancato et al. (2007)
Urinary elimination (K ELIM2 ; 1/hr) 0.5 Blancato et al. (2007)

TBA sequestration rate constant (K ON ; L/hr) 0.148 Optimized

TBA un sequestration rate constant (K OFF ; L/hr) 0.0134 Optimized
Absorption from gastrointestinal tract (K AS2 ; 1/hr) 0.5 Optimized

a scaled by BW 0.7 (0.25 0.7 = 0.379) , bw = body weight

.

Induction of t e rt

- butanol

- metabolizing enzymes was included in the Leavens and Borghoff (2009) model of MTBE based on their study of rats exposed for 8 days to t ert

- butanol via inhalation

. The enzyme induction equation and parameters developed in the Leavens and Borghoff (2009)
model t hat were applied to the tert

- butanol submodel are as follows.

Vmax t ert

- butanol IND = Vmax tert

- butanol *INDMAX(1

- exp(

- KIND*t))

Vmax t e rt

- butanol IND is the maximum metabolic rate after accounting for enzyme induction, Vmax

t e rt

- butanol is the metabolism rate constant from Table B-2 for both t ert

- butanol pathways, and INDMAX is the maximum percent increase in Vmax t e rt

- butanol (124.9)

. KIND is the rate constant for enzyme induction (0.3977/day). The increased t e rt

- butanol metabolism better estimates the
measured t e rt

- butanol blood concentrations as can be seen in the comparison of the model predictions and experimental measurements shown in Figure B-5 . The model better predicted
b lo od concentrations in female rats than male rats. The male rats ha d lower t ert

- butanol blood concentrations after repeated exposures compared w ith female rats

, and this difference could indicate greater induction of t e rt

- butanol metabolism or other physiologic changes such as ventilation or urinary excretion in males . The current data for t ert

- butanol metabolism do not provide sufficient information for resolving this difference between male and female rats.



### B .2.3. Summary of the PBPK model for tert -b utanol

A PBPK model for tert

- butanol was developed by adapting previous models for MTBE and

tert

- bu tanol ( Blancato et al. (2007) ; Leavens and Borghoff (2009) ). Published tert

- butanol models (or sub

- m odels) do not adequately represent the tert

- butanol blood concentrations measured in the i.v. study (Poet et al. 1997) . The addition of a sequestered blood compartment for tert

- butanol substantially improved the model fit. The alternative modification of changing to diffusion

- l imited distribution between blood and tissues also improved the model fit, but was considered l ess biologically plausible. Physiological parameters and partition coefficients were obtained from

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published measurements. The rate constants for tert

- butanol metabolism and elimination were 

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- butanol subc ompartment ( Blancato et al. (2007) ). Additional model parameters were estimated by calibrating to data sets for i.v., oral and inhalation exposures as well as repeated dosing studies for TBA. O v e rall, the model produced acceptable fits to multiple rat time

- c o urse datasets of TBA blood levels following either inhalation or oral gavage exposures.



### B.2.4. t e rt -B utanol Model Application The PBPK model as described above was applied to toxicity studies to predict t ert

- butanol blood concentrations (the preferred internal dose metric). For simulation studies where t e rt

bu tanol w as administered in d r inking water

, the consumption was modeled as episodic

, based on the pattern of drinking observed in rats ( Spiteri, 1982 ).



### B.2.5. P BPK Model Code The PBPK acslX model code is made available electronically through EPA’s Health and Environmental Research Online (HERO) database. All model files may be downloaded in a zipped worksp a ce from HERO (U.S. EPA, 201#, HEROID##).

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25
26 **Figure B-5.**  **Comparison of the EPA model predictions with measured amounts of** t ert

  ** butanol** **in blood after repeated inhalation**  **exposure to** tert

**- butanol** 

**.**
Male rats were exposed to 239, 444
, or 1726 ppm and female rats were exposed to 2 56 , 444
, or 1914 p pm tert

- butanol for up to 8 consecutive days ( Borghoff et al., 2001 ). tert -B utanol blood concentrations are better predicted by the model after 8 days of exposure w ith enzyme induction (right panels) compared to without enzyme i nduction (left panels).



## B.3. OTHER PERTINENT TOXICITY INFORMATION

B.3.1. Genotoxicity The g enotoxic potential of t ert

- butanol has been studied using a variety of g enotoxicity

assays , in cluding bacterial reverse mutation assays, gene mutation assays, chromosomal aberrations, sister chromatid exchanges, micronucleus formation, and DN A strand breaks and adducts. The available genotoxicity data for t e rt

- butanol are disc ussed below

, and the summary of the data is provided in Table B-3

.


### B .3.1.1. Bacterial Systems

The m utagenic potential of t ert

- butanol has been tested by Zeiger et al. (1987) using
different Sa lmonella typhimurium strains both in the presence and absence of S9 metabolic

activation. T he preincubation assay protocol was followed. Salmonella strains TA98, TA1 00, TA1535, TA1537, and T A1538 were exposed to five concentrations (100, 333, 1

, 000, 3
, 333, or 10,000 μg/plate) and tested in triplicate. No mutations were observed in any of the strains tested

, either in the presence or absence of S9 metabolic activation. Conflicting results have been obtained with t ert

- butanol

- induced mutagenicity in strain TA102, a strain that is sensitive to damage at A

- T s ites inducible by oxidants and other mutagens
and is e xcision

- repair proficient. In a study by Williams

- Hill et al. (1999)

, tert

- butanol induced an

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increase in the number of revertants in the first three concentrations with S9 activation in a dose



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38 response manner . The number of revertants decreased in the last two concentrations. No discussion was provided as to why the revertants decreased at higher concentrations. The results of this study indicate d that tester strain TA102 may be a more sensitive strain for monitoring t ert

butanol levels ( Williams

- Hill et al., 1999 ) . However, in another study by Mcgregor et al. (2005)

, experiments were conducted on Sa lmonella strain TA102 in two different laboratories using similar protocols

. t e rt -B utanol was dissolved in d ime thyl sulfoxide ( DMSO ) or distilled water and tested both in the presence and absence of S9 metabolic activation. No statistically significant increase in mutants was observed in either of the solvent media. In one experiment where t e rt

- butanol was dissolve d in water, a significant, dose

- related increase in the number of revertants was produced

, reaching almost two

- f old the control value at a concentration of 2

, 250 μg/plate. It should be noted that DMSO is known to be a free radical scavenger

, a nd its presence at high concentrations might mask a mutagenic response caused due to oxidative damage. Mutagenicity of t e rt

- butanol has been studied in other systems including Neurospora crassa
and S accharomyces cerevisiae

. Yeast strain Neurospora crass a at the ad

- 3A locus (allele 38701) was used to test the mutagenic activity of t e rt

- butanol at a concentration of 1.75 mol/L for 30 minutes.

t e rt -B utanol did not induce reverse mutations in the tested strain at the exposed concentration ( Dickey et al., 1949 ) . On the other hand

, tert

- butanol , without exog enous metabolic activation, significantly increased the frequency of petite mutations ( t he mitochondrial deoxyribonucleic acid [ DN A ] deletion rho− ) in Saccharomyces cerevisiae laboratory strains K5

- A5, MMY1, D517

- 4B, and
DS8 ( Jimenez et al., 1988 ). This effect on mitochondrial DNA, also observed with ethanol and other solvents, was attributed by the study authors to the alteration in the lipid composition of mitochondrial membranes, and m itochondrial DNA ’s close association could be affected by membrane composition ( Jimenez et al., 1988 ).



### B .3.1.2. In Vitro M ammalian Studies

To understand the role of t ert

- butanol

- induced genotoxicity in mammalian systems, in vitro studies have been conducted in different test systems and assays. t e rt -B utanol was tested to evaluate its ability to induce forward mutations at the t hymidine kinase locus (tk) in the L5178Y tk+/ - m ouse lymphoma cells using forward mutation assay. Experiments were conducted both in the presence and absence of S9 metabolic activation. The mutant frequency was calculated using
the ratio of mutant clones p er plate/total clones per plate × 200. t ert -B utanol did not reliably increase the frequency of forward mutations in L5178Y tk+/− mouse lymphoma cells with or without metabolic activation, although one experiment without addition of S9 yielded a small

inc re ase in mutant fraction at the highest tested concentration (5

, 000 μg/mL) ( McGregor et al.,
1988 ).
To further determine potential D NA and/or chromosomal damage induced by tert

- butanol

in i n vitro systems, ( NTP, 1995 ) studied sister chromatid exchanges (SCE s ) and chromosomal aberrations (CA s )

. Chinese h amster o vary (CHO) cells were exposed to t ert

- butanol both in the

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presence and absence of S9 activation at concentrations of 160

– 5,000 μg/ mL for 26 hours. t ert



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38 B utanol did not induce SCEs in any of the concentrations tested

, although in one experiment, there was a slight increase in percent relative change of SCEs per chromosome scored. The same authors
also studied the effect of t ert

- butanol on CA formation. CHO cells were exposed to four concentrations (160, 500, 1

, 600, or 5, 000 μg/m L ) of t ert

- butanol both in the presence and absence of S9. No significant increase in CAs was observed in any of the concentrations tested. It should be noted that due to severe toxicity at the highest concentration (5

, 000 μg/m L), only 13 metaphase cells were scored instead of 100 in the chromosomal aberration assay. Sgambato et al. (2009) examined the effects of t ert

- butanol o n DNA damage using normal diploid rat fibroblast cell line. C ells were treated with 0 - to 100 -mM t ert

- butanol for 48 hours to determine the half maximal inhibitory concentration (IC 50 ; 0.44 ± 0.2 mM ). The 48

- hour IC 50 concentration was then used to determine DNA content, cell number, and phases of the cell cycle after 24 and 48 hours of exposure. T otal protein and DNA oxidative damage were also measured. A comet assay was used to evaluate DNA fragmentation at time 0 an d after 30 minutes, 4 hours, or 12 hours of exposure to the IC 50 concentration. t ert -B utanol inhibited cell division in a dose

- dependent

manner a s measured by the number of cells after 24 and 48 hours of exposure at IC 50 concentrations
, a s well as with con centrations at 1/10th the IC 50
. There was no increase in cell death, suggesting a reduction in cell number due to reduced replication rather than cytotoxicity.

t e rt -B utanol caused an accumulation in the G 0 /G 1 phase of replication. These were related to
dif fe rent effects on the expression of cyclin D1

, p27Kip1 , and p53 genes

. An initial increase in DNA damage a s measured by nuclear fragmentation was observed at the 30

- minute timepoint. The DNA damage d eclined drastically after 4 hours and disappeared almost entirely after 12 hours of
exposure to t e rt

- butanol

. This reduction in the extent of DNA fragmentation after the initial increase is likely the result of an efficient DNA repair mechanism activated by cells following DNA damage induced by t e rt

- butan ol

. DNA damage caused by t er t

- butanol was determined by single

- cell gel electrophoresis (comet assay) in h uman promyelocytic leukemia (HL

- 60) cells

. The cells were exposed to

concentrations r anging from 1 to 30 mmol/L for 1 hour

, and a total of 100 cells w ere evaluated for DNA fragmentation. A d o se

- dependent increase in DNA damage was observed between 1 and
30 mm ol/L. No cytotoxicity was observed at the concentrations tested ( Tang et al., 1997 ).



### B .3.1.3. In Vivo Mammalian Studies

A l imited number of in vivo studies are available to understand the role of t ert

- butanol on genotoxicity. The National Toxicology Program studied the effect of t e rt

- butanol in a 13

- week toxicity study ( NTP, 1995 ) . Peripheral blood samples were obtained from male and female B6CF1 mice that were exposed to t e rt

- butanol in drinking water at doses of 3,000

– 40,000 ppm. Slides were prepared to det er mine the frequency of micronuclei in 10,000 normochromatic erythrocytes. In addition, the percentag e of polychromatic erythrocytes among the total erythrocyte population

w as d etermined. No increase in micronucleus formation in peripheral blood lymphocytes was

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observed either in male or female B6C3F 1 mice exposed for 13 weeks to t ert

- butanol in drinking 

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14 water at concentrations as high as 40,000 ppm (2,110 mg/kg

- day) ( NTP, 1995 ). Male Kumming mice ( 8 per treatment) were administered 0, 0.099, 0.99, 10, 101, or
997 μ g/kg bw 14 C- t ert

- butanol in saline via gavage with specific activity ranging from 1.60 to 0.00978 mCi/mol ( Yuan et al., 2007 ). Animals were sacrificed 6 hours after exposure

, and liver, kidney, and lung were collected. Ti ssues were prepared for DNA isolation with samples from the same organs from every two mice combined. DN A adducts were measured using accelerated mass spectrometry. T he results of this study show ed a dose

- response increase in DNA adducts in all three organs measured

, a lthough the methodology used to detect DNA adducts is considered sensitive but may be nonspecific

. T he authors state d that t ert

- butanol was found, for the first time, to form DNA adducts in mouse liver, lung

, a nd kidney. Because this is a single and first

- time study, further validation of this study will provide certainty in understanding the mechanism of t e rt

butanol

- i nduced DNA adducts.

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**Table B-3.**  **Summary of genotoxicity (both in vitro**  **and in vivo**  **) studie s of**  tert

**** 

### 1 2 **butanol**

**.**

Test system Dose/Conc. Results a Comments Reference
Bacterial Systems

- S9 + S9
Reverse Mutation Assay Salmonella typhimurium (TA98, TA100, TA1535, TA1537, TA1538) 100, 333, 1000, 3333, 10,000 μg/plate - - Preincubation procedure was followed. This study was part of the NTP 1995 testing results. Zeiger et al. (1987) ; NTP (1995)

Reverse Mutation Assay Salmonella typhimurium (TA102) 1 000

– 4 000
μ g/plate ND + Only tested with S9 activation Williams

- Hill et al. (1999)

Reverse Mutation Assay Salmonella typhimurium (TA98, TA100, TA102, TA1535, TA1537) 5 , 15, 50, 100, 150, 200, 500, 1000, 1500, 2500, 5000 μg/plate - - Experiments conducted in two different laboratories, two vehicles – distilled water and DMSO were used, different concentrations were used in experiments from different laboratories Mcgregor et al. (2005)

Reverse mutation Neurospora crassa , ad

- 3A locus (allele 38701) 1.75mol/L

- - Eighty four percent cell death was observed ; n ote it is a 1949 study Dickey et al. (1949)

Mitochondrial mutation Saccharomyces cerevisiae (K5

- 5A, MMY1, D517

- 4B
, and DS8) 4.0% (vol/vol) + b ND Mitochondrial mutations, membrane solvent Jimenez et al. (1988)

In vitro S ystems
Gene Mutation Assay, Mouse lymphoma cells L5178Y TK +/

– 625 , 1000, 1250, 2000, 3000, 4000, 5000 μ g/m L - - Cultures were exposed for 4 h, then cultured for 2 days before plating in soft agar with or without trifluorothymidine, 3 μg/mL ; this study was part of the NTP 1995 testing results McGregor et al. (1988) ; NTP (1995)

Sister

- chromatid exchange, Chinese Hamster Ovary cells 1 60, 500, 1600, 2000, 3000, 4000, 5 000 μ g/m L - - This study was part of the NTP 1995 testing results Galloway, 1987 ; NTP (1995)

Chromosomal Aberrations, Chinese Hamster Ovary cells 1 60, 500, 1600, 2000, 3000, 4000, 5 000 μ g/m L - - This study was part of the NTP 1995 testing results Galloway, 1987 NTP (1995)

DNA damage (comet assay), Rat fibroblasts 0.44 mmol/L (IC 50 ) + c N D Exposure duration

– 30 min, 4 h, 12 h; t his study provides other information on effect of cell cycle control genes and mechanism of action for TBA Sgambato et al. (2009)

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Test system Dose/Conc. Results a Comments Reference
DNA damage, (comet assay), h uman HL

- 60 leukemia cells 1 , 5, 10, 30 mmol/L + ND Exposure duration

– 1h Tang et al. (1997)

In vivo A nimal S tudies
Micronucleus formation, B6C3F1 mouse peripheral blood cells 3000, 5000, 10
, 000, 20
, 000, 40
, 000 ppm - 13

- week, subchronic, d rinking
water study NTP (1995)

DNA adducts, m ale Kunming mouse liver, kidney and lung cells 0.1

– 1000 μ g/kg body weight + Gavage, 6

- h exposure, DNA adduct determined by accelerator mass spectrometry Yuan et al. (2007)

a + = positive; − = negative; ND = not determined

. 

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. c DNA damage was completely reversed with increased exposure time

.



### B .3.2. Summary

t ert -B utanol has been tested for its genotoxic potential using a variety of genotoxicity assays. Bacterial assays that detect reverse mutations have been thought to predict carcinogenicity with accuracy up to 80 %

. t e rt -B utanol did not induce mutations in most bacterial strains ; however, when tested in TA102, a strain that is sensitive to damage at A

- T sites inducible by oxidants, an
increase in mutants w as observed at low concentrations, although conflicting results were reported in another study. F urthermore, the solv ent (e.g., distilled water or DMSO) used in the genotoxicity assay may impact results. I n one experiment where tert

- butanol was dissolved in distilled water, a significant, dose

- r elated increase in the number of mutants was observed, with the maximum value reaching almost 2- f old the control value. DMSO is known to be a radical scavenger

, and its presence in high concentrations might mask a mutagenic response m odulated by oxidative damage. Other species such as N eurospora crassa did not produce reverse mutations as a result of exposure to t ert

butanol

. tert

- B utanol was tested in several human and animal i n vitro mammalian systems for genotoxicity ( g ene mutation, sister chromatid exchanges, chromosomal aberrations

, and DNA damage ) . N o increase in gene mutations was observed in mouse lymphoma cells ( L5178Y TK +/

– ). These specific locus mutations in mammalian cells are used to demonstrate and quantify g enetic damage, thereby confirming or extending the data obtained in the more widely used bacterial cell

tests. S ister chromatid exchange or chromosomal aberrations were not observed in CHO cells in
response to tert

- b utanol treatment . However, DNA damage w as detected using comet assay in both
rat fibroblasts and human HL

- 6 0 leukemia cells, with either an increase in DNA fragmentation at the beginning of the exposure or dose

- d ependent increase in DNA damage observed

. An initial increase in DNA damage was obser ved at 30 min utes that declined drastically following 4 hours of exposure and disappeared almost entirely after 12 hours of exposure to t e rt

- butanol

. This reduction in the extent of DNA fragmentation after an i nitial increase is likely the result of an

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e fficient DNA repair mechanism activated by cells following DNA damage induced by t ert

- butanol . A 

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- repair mechanisms would occur after a longer period of observation

. Limited in vivo animal studies have been conducted on DNA adduct formation or
micronucleus formation

. A dose

- response increase in DNA adducts was observed in mou se liver, kidney, and lung cells

. Th e authors used accelerated mass spectrometry to detect DNA adducts , but

t h is method may be sensitive and not specific to the adducts in question . The method uses

14 C- labeled chemical for dosing

, and the isolated DNA is oxidized to carbon dioxide and reduced to filamentous graphite, and the ratios of 14 C/ 12 C are measured. The ratio is then converted to DNA adducts based on nucleotide content of the DNA, hence the debate for the reliability of the data obtained. Confirmation of this data will provide assurance in understanding the mechanism of

t e rt

- butanol

- induced DNA adducts. No increase in micronucleus formation was observed in mouse peripheral blood cells in a 13

- w eek drinking water study conducted by the National Toxicology Program. Overall, there is a li mited database to understand the role of t ert

- butanol

- induced genotoxicity for mode of action and carcinogenicity. T he database is limited either in terms of the array of genotoxicity tests condu ct ed or the number of studies within the same type of test. In addition, the results are either conflicting or inconsistent. The test s trains, solvents, or control for volatility used in certain studies are variable and may impact results. F urthermore, in some studies, the methodology used has been challenged for its specificity. G iven the inconsistencies and limitations of the database in terms of the methodology used, number of studies in the overall database, coverage of studies across the genotoxicity bat tery, and the quality of the studies

, the weight of evidence analysis is in conclusive. The available data do not inform a definitive conclusion on the genotoxicty of t ert

- butanol and thus the potential genotoxic effect s of t ert

- butanol cannot be
discounted

.

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# APPENDIX C. DOSE

- RESPONSE MODELING FOR 1

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# THE DERIVATION OF REFERENCE VALUES FOR EFFECTS OTHER THAN CANCER AND THE DERIVATION OF CANCER RISK ESTIMATES

C.1. BENCHMARK DOSE MODELING SUMMARY
This appendix provides technical detail on dose

- response evaluation and determination of points of departure (PODs) f or relevant endpoints. The endpoints were modeled using EPA’s Benchmark Dose Software (BMDS), v ersion 2.1.2

. The preambles for the cancer and noncancer parts below describe s t he common practices used in evaluating the model fit and selecting the appropriate model for determining the POD as outlined in the Benchmark Dose Technical Guidance
Document ( U.S. EPA, 2000 ). In some cases
, it may be appropriate to use alternative methods based
on statistical judgment ; exceptions are noted as necessary in the summary of the modeling results.



### C .1.1. Non c ancer Endpoints

C.1.1.1. Evaluation of Model Fit For each dichotomous endpoint, BMDS dichotomous models were fitted to the data using
the maximum likelihood method. E ach model was tested for goodness

- of

- fit using a chi

- square goodness

- of

- f

it test (χ 2 p

- value < 0.10 indicates lack of fit). Other factors were also used to assess model fit, such as scaled residuals, visual fit, and adequacy of fit in t h e low dose region and near the benchmark response ( B MR ). For each continuous endpoint, BMDS continuous models were fitted to the data using the
maximum likelihood method

, and m odel fit was assessed by a series of tests. For each model, first the homogenei ty of the variances was tested using a likelihood ratio test (BMDS Test 2). If Test 2 was not rejected (χ 2 p

- value ≥ 0.10), the model was fitted to the data assuming constant variance. If Test 2 was rejected (χ 2 p

- value < 0.10), the variance was modeled as a power function of the mean, and the variance model was tested for adequacy of fit using a likelihood ratio test (BMDS Test 3). For fitting models using either constant variance or modeled variance, models for the mean response were tested for adequacy o f fit using a likelihood ratio test (BMDS Test 4, with χ 2

p- va lue < 0.10 indicating inadequate fit). Other factors were also used to assess the model fit, such as scaled residuals, visual fit, and adequacy of fit in the low

- d ose region and near the BMR.



### C .1.1.2. Model Selection For each endpoint, the BMDL estimate (95% lower confidence limit on the BMD, as estimated by the profile likelihood method) and the A kaike’s information criterion ( AIC ) value were

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used to select a best

- fit model from among the models exhib iting adequate fit. If the BMDL 

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3
4

5 6 estimates were “sufficiently close,” that is, differed by at most 3- fold, the model selected was the one that yielded the lowest AIC value. If the BMDL estimates were not sufficiently close, the lowest
BMDL was selected as t he POD.

**Table C-1.**  **Non**

**- cancer endpoints selected for dose** 

**- response**  **modeling for**
t er t

**- butanol** 

Endpoint/Study Species /
Sex Doses and Effect Data Kidney transitional epithelial hyperplasia NTP (1995) Rat (F344) / M ale Dose (mg/kg

- d) 0 90 200 420
Incidence / Total 25 / 50 32 / 50 36 / 50 40 / 50

Kidney transitional epithelial hyperplasia NTP (1995) Rat (F344) / Female Dose (mg/kg

- d) 0 180 330 650
Incidence / Total 0 / 50 0 / 50 3 / 50 17 / 50

Mean relative kidney weight NTP (1995) Rat (F344) / M ale Dose (mg/kg

- d) 0 90 200 420
Mean ± SE (n) 3.68 ± 0.09 (10) 3.96 ± 0.13 (10) 4.22 ± 0.13 (10) 4.42 ± 0.15 (10) Mean relative kidney weight NTP (1995) Rat (F344) / Female Dose (mg/kg

- d) 0 180 330 650
Mean ± SE (n) 3.49 ± 0.08 (10) 3.99 ± 0.07 (10) 4.21 ± 0.08 (10) 4.95 ± 0.17 (10) Kidney inflammation NTP (1995) Rat (F344) / Female Dose (mg/kg

- d) 0 180 330 650 Incidence / Total 2 / 50 3 / 50 13 / 50 17 / 50
Thyroid follicular cell hyperplasia NTP (1995) Mouse (B6C3F 1 ) / Male Dose (mg/kg

- d) 0 540 1,040 2,070 Incidence / Total 5 / 60 18 / 59 15 / 59 18 / 57
Thyroid follicular cell hyperplasia NTP (1995) Mouse (B6C3F1) / Female Dose (mg/kg

- d) 0 510 1,020 2,110 Incidence / Total 19 / 58 28 / 60 33 / 59 47 / 59

Increased absolute kidney weight NTP (1997) Rat (F344) / Male Concentration (mg/m 3 ) 0 406 825 1643 3274 6369

Mean ± SD (n) 1.21 ± 0.082 (10) 1.21 ± 0.096

(9) 1.18 ± 0.079 (10) 1.25 ± 0.111 (10) 1.34 ± 0.054 (10) 1.32 ± 0.089 (10) Increased relative kidney weight NTP (1997) Rat (F344) / Male Concentration (mg/m 3 ) 0 406 825 1643 3274 6369

Mean ± SD (n) 3.68 ± 0.253 (10) 3.71 ± 0.12 (9) 3.64 ± 0.126 (10) 3.76 ± 0.19 (10) 3.96 ± 0.158 (10) 4 ± 0.158 (10)

This document is a draft for review purposes only and does not constitute Agency policy. 

### C-2 DRAFT

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### Supplemental Information― tert Butanol

Endpoint/Study Species /
Sex Doses and Effect Data Increased absolute kidney weight NTP (1997) Rat (F344) / Female Concentration (mg/m 3 ) 0 406 825 1643 3274 6369

Mean ± SD (n) 0.817 ± 0.136 (10) 0.782 ± 0.063

(10) 0.821 ± 0.061

(10) 0.853 ± 0.045 (10) 0.831 ± 0.054

(10) 0.849 ± 0.038

(10) Increased relative kidney weight NTP (1997) Rat (F344) / Female Concentration (mg/m 3 ) 0 406 825 1643 3274 6369

Mean ± SD (n) 4.00 ± 0.474 (10) 3.98 ± 0.190

(10) 4.03 ± 0.158

(10) 4.14 ± 0.126

(10) 4.09 ± 0.190

(10) 4.35 ± 0.095

(10)



### C.1.1.3. Modeling Results 1

2
3
4
5
6
7
8

9 10 11

12 13 14 Below are tables summarizing the modeling results for the noncancer endpoints modeled. The following parameter restrictions were applied, unless otherwise noted.

• D ichotomous models: For the log

- logistic and dichotomous Hill models, restrict slope ≥ 1; for the gamma and Weibull models, restrict power ≥ 1; fo r the multistage models,
restrict beta v alue s ≥ 0.

• C ontinuous models: For the polynomial models, restrict beta values ≥ 0; for the Hill, power, and exponential models, restrict power ≥ 1.

**Table C-**  **2**

**. Summary**  **of BMD modeling results for**  **k idney**  **t ransitional**  **e pithelial**  **h y**  **perplasia in male**  **F344 r ats**  **exposed to** t ert

**- butanol**  **in drinking water for 2 years**  **( NTP, 1995**  **) ; BMR**  **= 10% extra risk.**

Model a Goodness of fit BMD 10 (mg/kg

- d) BMDL 10 (mg/kg

- d) Basis for model selection p - value AIC
Log

- logistic 0.976 248.0 30 16 Log

- logistic model selected as best

- fitting model based on lowest AIC with all BMDL values sufficiently close (BMDLs differed by slightly more than 3- fold). Gamma 0.784 248.5 46 29

Logistic 0.661 248.8 58 41

Log

- probit 0.539 249.2 84 53

Multistage, 3 ° 0.784 248.5 46 29

Probit 0.633 248.9 60 43

Weibull 0.784 248.5 46 29

Dichotomous

- Hill 0.968 250.0 25 15

a Scaled residuals for selected model for doses 0, 90
, 200 , and 420 mg /kg -d were
– 0.076, 0. 147
, 0.046 , and

– 0.137
, respectively.

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### Supplemental Information― tert Butanol

1 2

3 0.4 0.5 0.6 0.7 0.8 0.9

0 50 100 150 200 250 300 350 400Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

17:16 05/13 2011 BMDL BMD Log-Logistic

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### C-4 DRAFT

— DO NOT CITE OR QUOTE **Figure C-1.**  **Plot of mean response by dose, with fitted curve for selected model.**

### Supplemental Information― tert Butanol

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 ==================================================================== Logistic Model. (Version: 2.13; Date: 10/28/2009) Input Data File: M: \ NCEA t

- Butanol \ BMD modeling \ BMDS Output \ 17 NTP 1995b_Kidney transitional epithelial hyperplasia, male rats_LogLogistic_10.(d) Gnuplot Plotting File: M: \ NCEA t

- Butanol \ BMD modeling \ BMDS Output \ 17 NTP 1995b_Kidney transitional epithelial hyperplasia, male rats_LogLogistic_10.plt Fri May 13 17:16:25 2011

====================================================================

[notes]

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The form of the probab ility function is:

P[response] = background+(1

- background)/[1+EXP(

- intercept

- slope*Log(dose))]

Dependent variable = Incidence Independent variable = Dose Slope parameter is restricted as slope >= 1

Total number of observations = 4 Total nu mber of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e

- 008 Parameter Convergence has been set to: 1e

- 008

User has chosen the log transformed model

Default Initial Parameter Values

background = 0.5 intercept = - 5.54788

slope = 1

Asymptotic Correlation Matrix of Parameter Estimates

( *** The model parameter(s) - slope have been estimated at a boun dary point, or have been specified by the user, and do not appear in the correlation matrix )

background intercept

background 1

- 0.71

intercept

- 0.71 1

Parameter Estimates

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit background 0.505366 * * * intercept - 5.58826 * * *

slope 1 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Deviance Test d.f. P- value Full model

- 121.996 4 Fitted model - 122.02 2 0.048148 2 0.9762 Reduced model

- 127.533 1 11.0732 3 0.01134

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### Supplemental Information― tert Butanol

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28

29 30 31 AIC: 248.04

Goodness of Fit Scaled
Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------------------------------

0.0000 0.5054 25.268 25.000 50 - 0.076 90.0000 0.6300 31.498 32.000 50 0.147 200.0000 0.7171 35.854 36.000 50 0.046 420.0000 0.8076 40.382 40.000 50 - 0.137

Chi^2 = 0.05 d.f. = 2 P- value = 0.9762

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 29.6967

BMDL = 15.6252

**Table C-3** 

**. Summary of BMD modeling results**  **for k**  **idney t**  **ransitional e**  **pithelial h**  **yperplasia in f**  **emale F**  **344 r ats**  **exposed to** t ert

**- butanol**  **in drinking water for 2 years**  **( NTP, 1995**  **); BMR = 10% extra risk.** 

Model a Goodness of fit BMD 10 (mg/kg

- d) BMDL 10 (mg/kg

- d) Basis for model selection p - value AIC

Gamma 0.83 91.41 409 334 Multistage 3 rd order model selected as best

- fitting model based on lowest AIC with all BMDL values sufficiently close (BMDLs differed by less than 3

- fold). Logistic 0.50 92.81 461 393

LogLogistic 0.79 91.57 414 333
LogProbit 0.89 91.19 400 327
Multistage 3° 0.92 89.73 412 339

Probit 0.62 92.20 439 372

Weibull 0.76 91.67 421 337

Dichotomous

- Hill N/A b 117.89 Error c Error c

a Scaled residuals for selected model for doses 0, 180, 330, and 650 mg/m 3 were 0.0,

– 0.664, 0.230, and 0.016, respectively.
b No available degrees of freedom to estimate a p

- value.

c BMD and BMDL computation failed for the Dichotomous

- Hill model.

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### Supplemental Information― tert Butanol

1 2

3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 0 0.1 0.2 0.3 0.4 0.5

0 100 200 300 400 500 600Fraction Affected

dose Multistage Model with 0.95 Confidence Level

17:18 05/13 2011 BMD BMDL Multistage

This document is a draft for review purposes only and does not constitute Agency policy. 

### C-7 DRAFT

— DO NOT CITE OR QUOTE **Figure C-2.**  **Plot of mean response by dose, with fitted curve for selected model.** 

==================================================================== Multistage Model. (Version: 3.2; Date: 05/26/2010)
Input Data File: M: \ NCEA 

### t ert

- butanol \ BMD modeling \ BMDS Output \ 20 NTP 1995b_Kidney transitional epithelial hyperplasia, female rats_Multi3_10.(d)
Gnuplot Plotting File: M: \ NCEA 

### t ert

- butanol \ BMD modeling \ BMDS Output \ 20 NTP 1995b_Kidney transitional epithelial hyperplasia, female rats_Multi3_10.plt Mon May 09 18:31:33 2011

=========================== =========================================

[notes]

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1

- background)*[1

- EXP(

- beta1*dose^1

- beta2*dose^2

- beta3*dose^3)]

The parameter betas are restricted to be positive

Dependent variable = Incidence Independent variable = Dose

Total number of observations = 4 Total number of records with missing values = 0 Total numb er of parameters in model = 4 Total number of specified parameters = 0 Degree of polynomial = 3

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e

- 008 Parameter Convergence has been set to: 1e

- 008

Defaul t Initial Parameter Values

Background = 0

Beta(1) = 0 Beta(2) = 1.51408e

- 007 Beta(3) = 1.29813e

- 009

Asymptotic Correlation Matrix of Parameter Estimates

### Supplemental Information― tert Butanol

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 ( *** The model parameter(s)

- Background

- Beta(1)

- Beta(2) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlation matrix )

Beta(3)

Beta(3) 1

Parameter Estimates

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0 * * *

Beta(1) 0 * * * Beta(2) 0 * * * Beta(3) 1.50711e

- 009 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Deviance Test d.f. P- value Full model

- 43.4002 4 Fitted model

- 43.8652 1 0.9301 3 0.8182 Reduced model

- 65.0166 1 43.2329 3 <.0001

AIC: 89.7304

Goodness of Fit Scaled
Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------------------------------

0.0000 0.0000 0.000 0.000 50 0.000 180.0000 0.0088 0.438 0.000 50 - 0.664 330.0000 0.0527 2.636 3.000 50 0.230 650.0000 0.3389 16.946 17.000 50 0.016

Chi^2 = 0.49 d.f. = 3 P- value = 0.9200

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 411.95

BMDL = 338.618

BMDU = 469.73

Taken together, (338.618, 469.73 ) is a 90 % two

- sided confidence interval for the BMD

This document is a draft for review purposes only and does not constitute Agency policy. 

### C-8 DRAFT

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### Supplemental Information― tert Butanol

1 2 3 **Table C-4**  **. Summary of BMD modeling results**  **for relative kidney weights in**  **male F344 rats**  **e xposed to**  t ert

**- butanol**  **in drinking water for 15 months (**  **NTP, 1995**  **) ; BMR = 10% relative deviation and 1 standard deviation.** 

Model a Goodness of fit BMD 10% (mg/kg

- d) BMDL 10% (mg/kg

- d) BMD 1SD (mg/kg

- d) BMDL 1SD (mg/kg

- d) Basis for model selection p - value AIC

Hill NA

- 27.27 120 39 124 45 Exponential (M4) is selected as the best

- fitting model based on visual fit at the low

- dose region. Exponential (M4) 0.854

- 29.23 117 48 123 53

Exponential (M5) N/A

- 27.27 121 48 126 54

Linear 0.421

- 29.54 222 155 229 161

Polynomial 0.421

- 29.54 222 155 229 161

Power 0.421

- 29.54 222 155 229 161

Exponential (M2) 0.365

- 29.25 236 170 243 176

Exponential (M3) 0.365

- 29.25 236 170 243 176

a Constant variance case presented (BMDS Test 2 p

- value = 0. 466 ), selected model in bold; scaled residuals for selected model for doses 0, 90
, 200
, 420 mg/kg -d were 0.04009
, - 0.1264 , 0.122, and

- 0.03578 , respectively.

This document is a draft for review purposes only and does not constitute Agency policy. 

### C-9 DRAFT

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### Supplemental Information― tert Butanol

1

2 3

4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42

This document is a draft for review purposes only and does not constitute Agency policy. 

### C- 10 DRAFT

— DO NOT CITE OR QUOTE **Figure C**  **-3. Plot of mean response by dose, with fitted curve for selected model**  **(10% relative deviation)** 

**.**

**==================================================================== Exponential Model. (Version: 1.7;**  **Date: 12/10/2009) Input Data File: M:**  **\ NCEA t** 

**- Butanol**  **\ BMD modeling**  **\ BMDS Output**  **\ 21 NTP**  **1995b_Mean relative kidney weight, male rats_ExpCV_10RD.(d )**  **Gnuplot Plotting File: M: \**  **NCEA t**

**- Butanol**  **\ BMD modeling**  **\ BMDS Output**  **\ 21 NTP**  **1995b_Mean relative kidney weight, male rats_ExpCV_10RD.plt Fri May 13 16:30:21 2011** 

**====================================================================**

**[notes]**

**~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~**

**The form of the response function by Model:**

**Model 2:** **Y[dose] = a * exp{sign * b * dose}** **Model 3:** **Y[dose] = a * exp{sign * (b * dose)^d}** **Model 4:** **Y[dose] = a * [c**

**- (c** 

**-** **1) * exp{**

**-** **b * dose}]** **Model 5:** **Y[dose] = a * [c**

**- (c** 

**-** **1) * exp{**

**-** **(b * dose)^d}]**

**Note: Y[dose] is the median response for exposure = dose; sign = +1 for increasing trend in data;**  **sign =**

**- 1 for decreasing trend.** 

**Model 2 is nested within Models 3 and 4. Model 3 is nested within Model 5.**  **Model 4 is nested within Model 5.**

**Dependent variable = Response Independent variable = Dose**  **Data are assumed to be distributed: normally** **Variance Model: exp(lnalpha +rho *ln** **(Y[dose])) rho is set to 0.**  **A constant variance model is fit.**

**Total number of dose groups = 4 Total number of records with missing values = 0**  **Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e** 

**- 008**  **Parameter Convergence has been set to: 1e** 

**- 008** 

### Supplemental Information― tert Butanol

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 **MLE solution provided: Exact**

**Initial Parameter Values**

**Variable Model 4** 

**-------- --------** 

**lnalpha -**  **1.93171**

**rho(S) 0** 

**a 3.496**  **b 0.00417714** 

**c 1.32752**  **d 1** 

**(S) = Specified**

**Parameter Estimates**

**Variable Model 4** 

**-------- -------**  **lnalpha**

**- 1.93087** 

**rho 0** 

**a 3.67517**  **b 0.00469937** 

**c 1.23673**  **d 1** 

**Table of Stats From Input Data**

**Dose N**  **Obs Mean Obs Std Dev** 

**----- ---**  **---------- -------------**  **0 10**  **3.68 0.2846**  **90 10**  **3.96 0.4111**  **200 10**  **4.22 0.4111**  **420 10**  **4.42 0.4743** 

**Estimated Values of Interest**

**Dose Est Mean**  **Est Std Scaled Residual** 

**------ ----------**  **--------- ----------------** 

**0 3.675**  **0.3808 0.04009**  **90 3.975**  **0.3808**

**- 0.1264**  **200 4.205**  **0.3808 0.1221**  **420 4.424**  **0.3808 -**  **0.03578**

**Other models for which likelihoods are calculated:**

**Model A1: Yij = Mu(i) + e(ij)**  **Var{e(ij)} = Sigma^2**

**Model A2: Yij = Mu(i) + e(ij)**  **Var{e(ij)} = Sigma(i)^2**

**Model A3: Yij = Mu(i) + e(ij)**  **Var{e(ij)} = exp(lalpha + log(mean(i)) * rho)**

**Model R:**  **Yij = Mu + e(i) Var{e(ij)} = Sigma^2** 

**Likelihoods of Interest**

**Model Log(likelihood)**  **DF AIC** 

**------- -----------------**  **---- ------------** 

This document is a draft for review purposes only and does not constitute Agency policy. 

### C- 11 DRAFT

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### Supplemental Information― tert Butanol

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56

57

58 **A1 18.63423**  **5 -**  **27.26846 A2**  **19.91058 8** 

**- 23.82116**  **A3 18.63423**  **5**

**- 27.26846** 
**R 10.08355**  **2**

**- 16.1671**  **4 18.61733**  **4 -**  **29.23465**

**Additive constant for all log**

**- likelihoods =**  **- 36.76.**  **This constant added to the above values gives the log** 

**- likelihood including the term that does not**  **depend on the model parameters.**

**Explanation of Tests**

**Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R)**  **Test 2: Are Variances Homogeneous? (A2 vs. A1)**  **Test 3: Are variances adequately modeled? (A2 vs. A3)** 

**Test 6a: Does Model 4 fit the data? (A3 vs 4)**

**Tests of Interest**

**Test**
**-** **2*log(Likelihood Ratio)** **D. F. p-**  **value**

**-------- ------------------------**  **------ --------------** 

**Test 1 19.65**  **6 0.00319**  **Test 2 2.553**  **3 0.4658**  **Test 3 2.553**  **3 0.4658**  **Test 6a 0.03381**  **1 0.8541** 

**The p**

**- value for Test 1 is less than .05.**  **There appears to be a difference between response and/or variances among the dose**  **levels, it seems appropriate to model the data.**

**The p**

**- value for Test 2 is greater than .1.**  **A homogeneous variance model appears to be appropriate here.** 

**The p**

**- value for Test 3 is greater than .1.**  **The modeled variance appears to be appropriate here.** 

**The p**

**- value for Test 6a is greater than .1.**  **Model 4 seems to adequately describe the data.** 

**Benchmark Dose Computations:**

**Specified Effect = 0.100000**

**Risk Type = Relative deviation** 

**Confidence Level = 0.950000**

**BMD = 116.807** 

**BMDL = 48.0466** 

This document is a draft for review purposes only and does not constitute Agency policy. 

### C- 12 DRAFT

— DO NOT CITE OR QUOTE

### Supplemental Information― tert Butanol

**Table C-5**  **. Summary of BMD modeling results**  **for relative kidney weights in**  

### 1 2 3 **female F344 rats**  **exposed to** t ert

**- butanol**  **in drinking water for 15 months (**  **NTP, 1995 )**  **; BMR = 10% relative deviation and 1 standard deviation.** 

Model a Goodness of fit BMD 10% (mg/kg

- d) BMDL 10% (mg/kg

- d) BMD 1SD (mg/kg

- d) BMDL 1SD (mg/kg

- d) Basis for model selection p - value AIC Exponential (M2) Exponential (M3) 0.48

- 49.14 178 154 108 80 The linear model was selected on the basis of the l owest AIC with all BMDL values for fitting models being sufficiently close (BMDLs differed by less than 3

- fold)

. Exponential (M4) Exponential (M5) 0.33

- 47.64 154 107 90 56

Hill 0.33

- 47.64 154 105 90 Error b

Linear Power 0.62

- 49.63 158 133 92 68

Polynomial 3° 0.33

- 47.63 158 133 98 68

a Modeled variance case presented (BMDS Test 2 p

- value = 0.0091), selected model in bold; scaled residuals for selected model for doses 0, 180, 330, and 650 mg/kg

- d were

- 0.383, 0.887,

- 0.411, and

- 0.105, respectively.
b The BMDL 1SD computation failed for the Hill model.

3.5

4 4.5

5 5.5

0 100 200 300 400 500 600Mean Response

dose Linear Model with 0.95 Confidence Level

16:36 05/13 2011 BMD BMDL Linear



### 4 5 6

7 8 9 10 **Figure C-4.**  **Plot of mean response by dose, with fitted curve for selected model (10%**  **relative deviation)**

**.**

==================================================================== Polynomial Model. (Version: 2.16; Date: 05/26/2010)
Input Data File: M: \ NCEA 

### t ert

- butanol \ BMD modeling \ BMDS Output \ 23 NTP 1995b_Mean relative kidney weight, female rats_Linear_10 RD.(d)

This document is a draft for review purposes only and does not constitute Agency policy. 

### C- 13 DRAFT

— DO NOT CITE OR QUOTE

### Supplemental Information― tert Butanol

Gnuplot Plotting File: M: \ NCEA 

### t ert

- butanol \ BMD modeling \ BMDS Output \ 23 NTP 

### 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 1995b_Mean relative kidney weight, female rats_Linear_10RD.plt Mon May 09 18:34:15 2011

====================================================================

[ notes]

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The form of the response function is:

Y[dose] = beta_0 + beta_1*dose + beta_2*dose^2 + ...

Dependent variable = Response Independent variable = Dose Signs of the polynomial coefficients are not restricted The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho)

Total number of dose groups = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e

- 008 Parameter Convergence has been set to: 1e

- 008

Default Initial Parameter Values lalpha = - 2.14986

rho = 0 beta_0 = 3.52312 beta_1 = 0.00219613

Asymptotic Correlation Matrix of Parameter Estimates

lalpha rho beta_0 beta_1

lalpha 1 -1 0.1

- 0.14

rho -1 1 - 0.1 0.14

beta_0 0.1 - 0.1 1

- 0.66

beta_1

- 0.14 0.14

- 0.66 1

Parameter Estimates

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

lalpha - 8.78559 2.23999

- 13.1759

- 4.39529

rho 4.47471 1.57167 1.39429 7.55513 beta_0 3.51492 0.0580177 3.40121 3.62864 beta_1 0.00223049 0.00022176 0.00179585 0.00266513

Table of Data and Estimated Values of Interest

Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res.

------ --- -------- -------- ----------- ----------- ----------

0 10 3.49 3.51 0.253 0.206 - 0.383 180 10 3.99 3.92 0.221 0.262 0.887 330 10 4.21 4.25 0.253 0.315 - 0.411 650 10 4.95 4.96 0.538 0.446 - 0.105

This document is a draft for review purposes only and does not constitute Agency policy. 

### C- 14 DRAFT

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### Supplemental Information― tert Butanol

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 Model Descriptions for likelihoods calculated

Model A1: Yij = Mu(i) + e(ij) Var{e(ij)} = Sigma^2

Model A2: Yij = Mu(i) + e(ij) Var{e(ij)} = Sigma(i)^2

Model A3: Yij = Mu(i) + e(ij) Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) Model A3 uses any fixed variance parameters that were specified by the user

Mod el R: Yi = Mu + e(i) Var{e(i)} = Sigma^2

Likelihoods of Interest

Model Log(likelihood) # Param's AIC

A1 25.104490 5 - 40.208981 A2 30.882250 8 - 45.764500 A3 29.295765 6 - 46.591531 fitted 28.815603 4 - 49.631206

R - 0.698257 2 5.396514

Explanation of Tests

Test 1: Do responses and/or variances differ among Dose levels? (A2 vs. R) Test 2: Are Variances Homogeneous? (A1 vs A2) Test 3: Are variances adequately modeled? (A2 vs. A3) Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) (Note: When rho=0 the results of Test 3 and Test 2 will be the same.)

Tests of Interest

Test

- 2*log( Likelihood Ratio) Test df p- value

Test 1 63.161 6 <.0001 Test 2 11.5555 3 0.009072 Test 3 3.17297 2 0.2046 Test 4 0.960325 2 0.6187

The p

- value for Test 1 is less than .05. There appears to be a difference between response and/or variances among the dose levels It seems appropriate to model the data

The p

- value for Test 2 is less than .1. A non

- homogeneous variance model appears to be appropriate

The p

- value for Test 3 is greater than .1. The modeled variance appears

to be appropriate here

The p

- value for Test 4 is greater than .1. The model chosen seems to adequately describe the data Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Relative risk

Confidence level = 0.95

BMD = 157.585

BMDL = 132.699

This document is a draft for review purposes only and does not constitute Agency policy. 

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### Supplemental Information― tert Butanol

**Table C-6.**  **Summary of BMD modeling results for**  **kidney inflammation in** 

### 1 2 3 **female rats exposed to**  t ert

**- butanol**  **in drinking water for 2 years (**  **NTP, 1995 )**  **; BMR = 10% extra risk.** 

Model a Goodness of fit BMD 10% (mg/kg

- d) BMDL 10% (mg/kg

- d) Basis for model selection p - value AIC

Gamma 0.084 169.9 231 135 LogProbit was s elected on the basis of the lowest AIC with all BMDL values for fitting models being sufficiently close (BMDLs differed by less than 3

- fold)

. Logistic 0.082 169.7 305 252
LogLogistic 0.092 169.8 228 124
LogProbit 0.243 167.6 254 200
Multistage 3° 0.072 170.3 216 132

Probit 0.108 169.2 285 235

Weibull 0.081 170.0 226 134

Dichotomous

- Hill N/A b 169.5 229 186

a S elected model in bold; scaled residuals for selected model for doses 0, 180, 330, and 650 mg/kg

- d were

- 0.067,

- 0.700, 1.347, and

- 0.724, respectively.
b No available degrees of freedom to estimate a p

- value.



### 4 5

6 7 8 9 10 11 12 13 0 0.1 0.2 0.3 0.4 0.5

0 100 200 300 400 500 600Fraction Affected

dose LogProbit Model with 0.95 Confidence Level

17:17 05/13 2011 BMDL BMD LogProbit

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— DO NOT CITE OR QUOTE **Figure C-5.**  **Plot of mean response by dose, with fitted curve for selected model.** 

==================================================================== Probit Model. (Version: 3.2; Date: 10/28/2009)
Input Data File: M:/NCEA 

### t ert

- butanol /BMD modeling/BMDS Output/19 N TP 1995b_Kidney inflammation, female rats_LogProbit_10.(d)
Gnuplot Plotting File: M:/NCEA 

### t ert

- butanol /BMD modeling/BMDS Output/19 NTP 1995b_Kidney inflammation, female rats_LogProbit_10.plt Fri May 13 17:17:59 2011

=========================== =========================================

### Supplemental Information― tert Butanol

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 [notes]

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = Background + (1

- Background) * CumNorm(Intercept+Slope*Log(Dos e)),

where CumNorm(.) is the cumulative normal distribution function

Dependent variable = Incidence Independent variable = Dose Slope parameter is restricted as slope >= 1

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e

- 008 Parameter Convergence has been set to: 1e

- 008

User has chosen the log transformed model

Default Initial (and Specified) Parameter Values

background = 0.04 intercept = - 8.01425

slope = 1.18928

Asymptotic Correlation Matrix of Parameter Estimates

( *** The model parameter(s)

- slope

h ave been estimated at a boundary point, or have been specified by the user,

and do not appear in the correlation matrix )

background intercept

background 1

- 0.51

intercept

- 0.51 1

Parameter Estimates

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit background 0.0381743 0.0246892

- 0.0102155 0.0865642 intercept - 6.82025 0.161407 - 7.1366 - 6.5039

slope 1 NA

NA - Indicates that this parameter has hit a bound implied by some inequality constraint and thus has no standard error.

Analysis of Deviance Table

Model Log(likelihood) # Param's Deviance Test d.f. P- value Full model

- 80.4502 4 Fitted model

- 81.8218 2 2.7432 2 0.2537 Reduced model

- 92.7453 1 24.5902 3 <.0001

AIC: 167.644

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### Supplemental Information― tert Butanol

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Goodness of Fit Scaled
Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------------------------------

0.0000 0.0382 1.909 2.000 50 0.067 180.0000 0.0880 4.402 3.000 50 - 0.700 330.0000 0.1859 9.295 13.000 50 1.347 650.0000 0.3899 19.495 17.000 50 - 0.724

Chi^2 = 2.83 d.f. = 2 P- value = 0.2427

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 254.347

BMDL = 199.789

This document is a draft for review purposes only and does not constitute Agency policy. 

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### Supplemental Information― tert Butanol

**Table C-7.**  **Summary of BMD modeling results for**  **thyroid follicular cell** 

### 1 2 3 **hyperplasia in male**  **B6C3F1 mice exposed to**  t ert

**- butanol**  **in drinking water for 2 years**  **( NTP, 1995**  **) ; BMR = 10% extra risk.** 

Model a Goodness of fi t BMD 10% (mg/kg

- d) BMDL 10% (mg/kg

- d) Basis for model selection p - value AIC

Gamma 0.052 254.7 702 430 No model was selected as a best

- fitting model as models did not fit the overall goodness

- of

- fit criterion. Logistic 0.031 256.1 1,064 751
LogLogistic 0.069 254.1 586 340
LogProbit 0.012 258.2 1,320 810
Multistage 3° Weibull 0.052 254.7 702 430

Probit 0.032 255.9 1,020 713

Dichotomous

- Hill N/A b 253.6 0.19 Error c

a No model was se lected as a best

- fitting model.
b No available degrees of freedom to estimate a p

- value.

c BMDL computation failed for the Dichotomous

- Hill model. 

### 4

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### Supplemental Information― tert Butanol

**Table C-8** 

**. Summary of BMD modeling results for**  **thyroid follicular cell hyperplasia in female**  **B6C3F1 mice**  **exposed to** t ert

**- butanol**  **in drinking water for 2 years**  **( NTP, 1995**  **) ; BMR = 10% extra**  **risk.** 

### 1 2 3

Model a Goodness of fit BMD 10 (mg/kg

- d) BMDL 10 (mg/kg

- d) Basis for model selection p- value AIC

Gamma 0.63 303.1 327 154 The probit model was s elected on the basis of the l owest AIC with all BMDL values for fitting models being sufficiently close (BMDLs differed by less than 3

- fold)

. Logistic 0.94 301.0 297 243
LogLogistic 0.52 303.2 375 115
LogProbit 0.48 303.3 388 277
Multistage 3° 0.81 302.9 269 155

Probit 0.95 300.9 298 246

Weibull 0.66 303.0 321 154

Dichotomous

- Hill 0.66 27,226 b Error b Error

a S elected model in bold; scaled residuals for selected model for doses 0, 510, 1,020, and 2,110 mg/kg

- d were

- 0.110, 0.255,

- 0.174, and 0.025, respectively.
b The BMD and BMDL computations failed for the Dichotomous

- Hill model.

0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

0 500 1000 1500 2000Fraction Affected

dose Probit Model with 0.95 Confidence Level

18:36 05/09 2011 BMDL BMD Probit



### 4 5

6 7 8 9 10 11 12 **Figure C-6.**  **Plot of mean response by dose, with fitted curve for selected model.**

==================================================================== Probit Model. (Version: 3.2; Date: 10/28/2009)
Input Data File: M: \ NCEA 

### t ert

- butanol \ BMD modeling \ BMDS Output \ 27 NTP 1995b_Thyroid follicular cell hyperplasia, female mice_Probit_10.(d)
Gnuplot Plotting File: M: \ NCEA 

### t ert

- butanol \ BMD modeling \ BMDS Output \ 27 NTP 1995b_Thyroid follicular cell hyperplasia, female mice_Probit_10.plt Mon May 09 18:36:50 2011

This document is a draft for review purposes only and does not constitute Agency policy. 

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### Supplemental Information― tert Butanol

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 ====================================================================

[notes]

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = CumNorm(Intercept+Slope*Dose),

where CumNorm(.) is the cumulative normal distribution function

Dependent variable = Incidence Independent variable = Dose Slope parameter is not restricted

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e

- 008 Parameter Convergence has been set to: 1e

- 008

Default Initial (and Specified) Parameter Values

background = 0 Specified intercept =

- 0.425261

slope = 0.000589168

Asymptotic Correlation Matrix of Parameter Estimates

( *** The model parameter(s)

- background have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlation matrix )

intercept slope

intercept 1

- 0.76

slope

- 0.76 1

Parameter Estimates

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit intercept

- 0.427828 0.129459 - 0.681563 - 0.174092

slope 0.000593756 0.00011419 0.000369947 0.000817564

Analysis of Deviance Table

Model Log(likelihood) # Param's Deviance Test d.f. P- value Full model

- 148.416 4 Fitted model

- 148.47 2 0.108205 2 0.9473 Reduced model

- 162.896 1 28.9589 3 <.0001

AIC: 300.941

Goodness of Fit Scaled
Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------------------------------

0.0000 0.3344 19.395 19.000 58 - 0.110 510.0000 0.4503 27.015 28.000 60 0.255 1020.0000 0.5706 33.663 33.000 59 - 0.174 2110.0000 0.7953 46.923 47.000 59 0.025

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### Supplemental Information― tert Butanol

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Chi^2 = 0.11 d.f. = 2 P- value = 0.9473

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 297.997

BMDL = 246.075

This document is a draft for review purposes only and does not constitute Agency policy. 

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### Supplemental Information― tert Butanol

**Table C-9** 

**. Summary of BMD modeling results for absolute kidney weight in**  **male F344 rats exposed to** t ert

**- butanol**  **via inhalation for 6 hr**  **/d, 5d/wk for 13 weeks**  **( NTP, 1997**  **) ; BMR = 10% relative deviation from the mean.**  

### 1 2 3

4
Model a Goodness of fit BM C 10RD 3 ) (mg/m BM CL 10RD 3 ) (mg/m Basis for model selection

p - value AIC
Exponential (M2) <0.0001

- 205.06 b error b error The Hill model was selected as the only adequately

- fitting model

. Exponential (M3) <0.0001

- 203.06 9.2E+07 7094
Exponential (M4) < 0.0001

- 203.06 b error 0
Exponential (M5) <0.0001

- 201.06 b error 0

Hill 0.763

- 226.82 1931 1705

c Power 0.0607

- 220.97 5364 3800 Linear
Polynomial 5° d Polynomial 4° e Polynomial 3° 1.44E

04 - 207.06

- 9999 f error

Polynomial 2° 1.44E

04 - 207.06

- 9999 18436

a Constant variance case presented (BMDS Test 2 p

- value = 0.390), selected model in bold; scaled residuals for selected model for doses 0, 406, 825, 1643, 3274, and 6369 mg/m 3 were 0.395, 0.374,

- 0.75,

- 1.96e

- 006, 0.381, and

- 0.381, respectively.
b BMC or BMCL computation failed for this model.

c For the Power model, the power parameter estimate was 1. The models in this row reduced to the Linear model.
d For the Polynomial 5° model, the b5 and b4 coefficient estimates were 0 (boundary of parameters space). The models in this row reduced to the Polynomial 3° model.

e For the Polynomial 4° model, the b4 coefficient estimate was 0 (boundary of parameters space). The models in this row reduced to the Polynomial 3° model.
f BMC or BMCL computation failed for this model



### 5

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### Supplemental Information― tert Butanol

1 2

3 4

5 6 7 8 9 10 11 12 13 14 15

16 17 1.1 1.15

1.2 1.25

1.3 1.35

1.4

0 1000 2000 3000 4000 5000 6000Mean Response

dose Hill Model with 0.95 Confidence Level

10:15 04/30 2014 BMD BMDL Hill

This document is a draft for review purposes only and does not constitute Agency policy. 

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— DO NOT CITE OR QUOTE **Figure C-7**  **. Plot of mean response by dose, with fitted curve for selected model; dose shown in mg/m**  **3**

**.**

**Hill Model.** (V er sion: 2.15; Date: 10/28/2009) The form of the response function is: Y[ dose] = intercept + v*dose^n/(k^n + dose^n) A constant variance model is fit

**Benchmark Dose Computation.** BMR = 10% Relative risk BMD = 1931.35 BMDL at the 95% confidence level = 1704.82

**Parameter Estimates**
Variable Estimate Default Initial Parameter Values
alpha 0.00687349 0.00750263

rho n/a 0
intercept 1.19966 1.21

v 0.130345 0.13

n 18 18

k 1685.82 4451.94

### Supplemental Information― tert Butanol

**Table of Data and Estimated Values of Interest** 

### 1

2 3

4 5

6 7 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Resid

0 10 1.21 1.2 0.0822 0.0829 0.395

406 9 1.21 1.2 0.096 0.0829 0.374

825 10 1.18 1.2 0.0791 0.0829

- 0.75

1643 10 1.25 1.25 0.111 0.0829

- 0.00000196

3274 10 1.34 1.33 0.0538 0.0829 0.381

6369 10 1.32 1.33 0.0885 0.0829

- 0.381

**Likelihoods of In**  **terest**
Model Log(likelihood) # Param's AIC

A1 117.992549 7

- 221.985098

A2 120.600135 12

- 217.20027

A3 117.992549 7

- 221.985098

fitted 117.41244 4

- 226.82488

R 105.528775 2

- 207.05755

**Tests of Interest**

Test

- 2*log(Likelihoo d Ratio) Test df p- value

Test 1 30.1427 10 0.0008118

Test 2 5.21517 5 0.3902

Test 3 5.21517 5 0.3902

Test 4 1.16022 3 0.7626

This document is a draft for review purposes only and does not constitute Agency policy. 

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### Supplemental Information― tert Butanol

**Table C-**  **10**

**. Summary of BMD modeling results for**  **relative kidney weight in**  **male F344 rats exposed to** t ert

**- butanol**  **via inhalation for 6 hr**  **/d, 5d/wk for 13 weeks**  **( NTP, 1997**  **) ; BMR = 10% relative deviation from the mean.**  

### 1 2 3

4
Model a Goodness of fit BM C 10RD 3 ) (mg/m BMC L 10RD 3 ) (mg/m Basis for model selection

p - value AIC
Exponential (M2) Exponential (M3) b 0.168

- 141.06 6356 4923 The linear model is selected on the basis of l owest AIC

. Exponential (M4) 0.169

- 140.46 5973 3386
Exponential (M5) 0.560

- 142.35 c error 0

Hill 0.612

- 142.53 c error c error

d Power Polynomial 5° e Polynomial 4° f Polynomial 3° g Polynomial 2° h
Linear 0.181

- 141.25 6309 4821

a Constant variance case presented (BMCS Test 2 p

- value = 0.165), selected model in bold; scaled residuals for selected model for doses 0, 406, 825, 1643, 3274, and 6369 mg/m3 were 0.181, 0.282,

- 1.42,

- 0.102, 1.81, and

- 0.736, respectively.
b For the Exponential (M3) model, the estimate of d was 1 (boundary). The models in this row reduced to the Exponential (M2) model.

c BMC or BMCL computation failed for this model.
d For the Power model, the power parameter estimate was 1. The models in this row reduced to the Linear model.

e For the Polynomial 5° model, the b5, b4, and b3 coefficient estimates were 0 (boundary of parameters space). The models in this row reduced to the Polynomial 2° model. For the Polynomial 5° model, the beta coefficient estimates were 0 (boundary of parameters space). The models in this row reduced to the Linear model.
f For the Polynomial 4° model, the b4 and b3 coefficient estimates were 0 (boundary of parameters space). The models in this row reduced to the Polynomial 2° model. For the Polynomial 4° model, the b4, b3, and b2 coefficient estimates were 0 (boundary of parameters space). The models in this row reduced to the Linear model.

g For the Polynomial 3° model, the b3 coefficient estimates was 0 (boundary of parameters space). The models in this row reduced to the Polynomial 2° model. For the Polynomial 3° model, the b3 and b2 coefficient estimates were 0 (boundary of parameters space). The m odels in this row reduced to the Linear model.
h For the Polynomial 2° model, the b2 coefficient estimate was 0 (boundary of parameters space). The models in this row reduced to the Linear model.



### 5

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### Supplemental Information― tert Butanol

1 2 3 4

5 6 7 8 9 10 11 12 13 14 15

16 17 3.5 3.6 3.7 3.8 3.9

4 4.1

0 1000 2000 3000 4000 5000 6000Mean Response

dose Linear Model with 0.95 Confidence Level

10:24 04/30 2014 BMD BMDL Linear

This document is a draft for review purposes only and does not constitute Agency policy. 

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— DO NOT CITE OR QUOTE **Figure C-8**  **. Plot of mean response by dose, with fitted curve for selected model; dose shown in mg/m**  **3**

**.**

**Polynomial Model.** ( V ersion: 2.16; Date: 05/26/2010) The form of the response function is: Y[ dose] = beta_0 + beta_1*dose A constant variance model is fit

**Benchmark Dose Computation.** BMR = 10% Relative risk BMD = 6308.98 BMDL at the 95% confidence level = 4820.9

**Parameter Estimates**
Variable Estimate Default Initial Parameter Values
alpha 0.0303258 0.0303618

rho n/a 0
beta_0 3.67004 3.67051
beta_1 0.0000581717 0.000058076

**Table of Data and Estimated Values of Interest**

Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Resid

0 10 3.68 3.67 0.253 0.174 0.181

406 9 3.71 3.69 0.12 0.174 0.282

825 10 3.64 3.72 0.126 0.174

- 1.42

1643 10 3.76 3.77 0.19 0.174

- 0.102

### Supplemental Information― tert Butanol

3274 10 3.96 3.86 0.158 0.174 1.81

6369 10 4 4.04 0.158 0.174

- 0.736 

### 1 2

3 4

5 6

7 **Likelihoods of Interest**
Model Log(likelihood) # Param's AIC

A1 76.753535 7

- 139.507071

A2 80.677068 12

- 137.354137

A3 76.753535 7

- 139.507071

fitted 73.624808 3

- 141.249616

R 60.931962 2

- 117.863925

**Tests of Interest**

Test

- 2*log(Likelihoo d Ratio) Test df p - value

Test 1 39.4902 10 <0.0001

Test 2 7.84707 5 0.1649

Test 3 7.84707 5 0.1649

Test 4 6.25745 4 0.1807

This document is a draft for review purposes only and does not constitute Agency policy. 

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### Supplemental Information― tert Butanol

**Table C-**  **11 . Summary of BMD modeling results for**  **absolute kidney weight in**  

### 1 2 3 **fe male F344 rats exposed to**  t ert

**- butanol**  **via inhalation for 6 hr**  **/d, 5d/wk for 13 weeks**  **( NTP, 1997**  **) ; BMR = 10% relative deviation from the mean.** 

Model a Goodness of fit BMC 10RD (mg/m 3 ) BMC L 10RD (mg/m 3 ) Basis for model selection

p - value AIC
Exponential (M2) Exponential (M3) b 0.0378

- 261.52 14500 7713 No model adequately fit the data.
Exponential (M4) 0.533

- 267.48 error c 0
Exponential (M5) 0.374

- 265.71 error c 0

Hill 0.227

- 265.57 error c error c

Power 0.0392

- 261.61 14673 7678
Polynomial 3° d Polynomial 2° e
Linear 0.0274

- 261.61 14673 7678

Polynomial 5° 0.0274

- 261.61 14673 7569
Polynomial 4° 0.0274

- 261.61 14673 7674

a Modeled variance case presented (BMDS Test 2 p

- value = 1.90E

- 04, BMDS Test 3 p

- value = 0.374), no model was selected as a best

- fitting model.
b For the Exponential (M3) model, the estimate of d was 1 (boundary). The models in this row reduced to the Exponential (M2) model.

c BMC or BMCL computation fa iled for this model.
d For the Polynomial 3° model, the b3 coefficient estimates was 0 (boundary of parameters space). The models in this row reduced to the Polynomial 2° model. For the Polynomial 3° model, the b3 and b2 coefficient estimates were 0 (boundary of parameters space). The models in this row reduced to the Linear model.

e For the Polynomial 2° model, the b2 coefficient estimate was 0 (boundary of parameters space). The models in this row reduced to the Linear model.



### 4 5

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### Supplemental Information― tert Butanol

**Table C-**  **12 . Summary of BMD modeling results for relative kidney weight in**  

### 1 2 3 **fe male F344 rats exposed to**  t ert

**- butanol**  **via inhalation for 6 hrs/d, 5d/wk for 13 weeks**  **( NTP, 1997**  **) ; BMR = 10% relative deviation from the mean.** 

Model a Goodness of fit BM C 10RD (mg/m 3 ) BMC L 10R D (mg/m 3 ) Basis for model selection

p - value AIC
Exponential (M2) Exponential (M3) b 0.813

- 125.14 6859 5476 No model adequately fit the data.
Exponential (M4) c 0.660

- 123.12 6846 4832
Exponential (M5) d 0.660

- 123.12 6846 4832

Hill 0.00189

- 123.12 6845 5380

Power 0.809

- 125.12 6846 5389
Polynomial 3° 0.00210

- 123.34 6853 5439
Polynomial 2° 0.00191

- 123.14 6865 5393

Linear 0.00488

- 125.12 6846 5389
Polynomial 5° 0.00238

- 123.61 6762 5504
Polynomial 4° 0.00228

- 123.51 6807 5480

a Modeled variance case presented (BMDS Test 2 p

- value = <0.0001, BMDS Test 3 p

- value = 0.00105), no model was selected as a best

- fitting model.
b For the Exponential (M3) model, the estimate of d was 1 (boundary). The models in this row reduced to the Expo nential (M2) model.

c The Exponential (M4) model may appear equivalent to the Exponential (M5) model, however differences exist in digits not displayed in the table.
d The Exponential (M5) model may appear equivalent to the Exponential (M4) model, however differences exist in digits not displayed in the table. 

### 4

C.1.2. Cancer Endpoints 5

6
7
8
9
10
11
12
13
14 For each endpoint, multistage models were fitted to the data using the maximum likelihood
method. Each model was tested for goodness

- of

- f

it

using a chi

- square goodness

- of

- fit test (χ 2

p

- value < 0.05 1 indicates lack of fit). Other factors were used to assess model fit, such as scaled residuals, visual fit, and adequacy of fit in the low do s e region and near the BMR. For each endpoint, the BMDL estimate (95% lower confidence limit on th e B MD, as estimated by the profile likelihood method) and AIC value were used to select a best

- fi t model from among the models exhibiting adequate fit. If t h e BMDL estimates were “sufficiently close,” that is, differed by more than 3- fo l d, the model selected was the one that yielded the lowest AIC value. If the BMDL estimates were not sufficiently close, the lowest BMDL was selected as the POD. For t he

1 A significance level of 0.05 is used for selecting cancer models because the model family (multistage) is selected a priori ( U.S. EPA, 2000 ).

This document is a draft for review purposes only and does not constitute Agency policy. 

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### Supplemental Information― tert Butanol

NTP (1995) and Hard et al. (2011) data, models were run with all doses included, as well as with 

### 1
2
3

4 5

6

7

8
9
10
11 the high dose dropped. Dropping the high dose resulted in a better fit to the data. Including the high
dose caused the model to overestimate the control.

**Table C** 

**- 13** 

**. C**  **ancer endpoints selected for dose**

**- response modeling for**  t ert

**** **butanol**

Endpoint/Study Species / Sex Doses and Effect Data Renal tubule adenoma or carcinoma NTP (1995) Rat (F344) / Male Dose (mg/kg

- d) 0 90 200 420
Incidence / Total 8 / 50 13 / 50 19 / 50 13 / 50

Renal tubule adenoma or carcinoma NTP (1995) Rat (F344) / Male Dose (PBPK, mg/L ) 0 4.6945 12.6177 40.7135
Incidence / Total 8 / 50 13 / 50 19 / 50 13 / 50

Renal tubule adenoma or carcinoma NTP (1995) Ra t (F344) / Male Dose (PBPK, mg/hr) 0 0.7992 1.7462 3.4712
Incidence / Total 8 / 50 13 / 50 19 / 50 13 / 50

Renal tubule adenoma or carcinoma; Hard reanalysis NTP (1995) ; Hard et al. (2011) Rat (F344) / Male Dose (mg/kg

- d) 0 90 200 420
Incidence / Total 4 / 50 13 / 50 18 / 50 12 / 50

Renal tubule adenoma or carcinoma; Hard reanalysis NTP (1995) ; Hard et al. (2011) Rat (F344) / Male Dose (PBPK, mg/L ) 0 4.6945 12.6177 40.7135
Incidence / Total 4 / 50 13 / 50 18 / 50 12 / 50

Renal tubule adenoma or carcinoma; Hard reanalysis NTP (1995) ; Hard et al. (2011) Rat (F344) / Male Dose (PBPK, mg/hr) 0 0.7992 1.7462 3.4712
Incidence / Total 4 / 50 13 / 50 18 / 50 12 / 50

Thyroid follicular cell adenoma NTP (1995) B6C3F 1 mice / female Dose (mg/kg

- d) 0 510 1,020 2,110

Incidence / Total 2 / 58 3 / 60 2 / 59 9 / 59



### C.1.2.1. M odeling Results Below are tables summarizing the modeling results for the cancer endpoints that were
modeled. For the multistage models, the coefficients were restricted to be non

- n eg ative (beta
value s ≥ 0).

This document is a draft for review purposes only and does not constitute Agency policy. 

### C- 31 DRAFT

— DO NOT CITE OR QUOTE

### Supplemental Information― tert Butanol

**Table C-**  **14**

**. Summary of BMD modeling results for**  **r enal tubule adenoma or**  

### 1 2 3 4

5 **carcinoma in male F344 rats exposed to**  t ert

**- butanol**  **in drinking water for 2 years modeled with administered dose units and including all dose groups**  **( NTP**  **, 1995 )**  **; BMR = 10% extra risk.**

Model a Goodness of fit BMD 10Pct (mg/kg

d) BMDL 10Pct (mg/kg

- d) Basis for model selection p value Scaled residuals AIC

Three Two 0.080 6 - 0.989, 0.288, 1.719, and

- 1.010 233.9 4 294 118 Multistage 2° is selected as the
most parsimonious model of adequate fit. One 0.080 6 - 0.989, 0.288, 1.719, and

- 1.010 233.9 4 294 error b

a Selected model in bold.
b BMD or BMDL computation failed for this model.



### 6

7 8 9 10

11 0.1 0.2 0.3 0.4 0.5

0 50 100 150 200 250 300 350 400Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

10:57 04/30 2014 BMD BMDL Multistage Cancer Linear extrapolation

**Figure C-9**  **. Plot of incidence rate by dose, with fitted curve for selected model; dose**  **shown in mg/kg**

**- d.** 

This document is a draft for review purposes only and does not constitute Agency policy. 

### C- 32 DRAFT

— DO NOT CITE OR QUOTE

### Supplemental Information― tert Butanol

**Multistage Cancer Model.** (Version: 1.9; Date: 05/26/2010) 

### 1 2 3 4 5 6 7 8 9 10 11 12 13 14

15 16

17 18 19 20

21 22 23 24 The form of the probability function is: P[response] = background + (1

- background)*[1

- EXP(

- beta1*dose^1

- bet a2 *dose^2...)] The parameter betas are restricted to be positive

**Benchmark Dose Computation.** BMR = 10% Extra risk BMD = 293.978 BMDL at the 95% confidence level = 117.584 BMDU at the 95% confidence level = 543384000 Taken together, (117.584, 543384000) is a 9 0% t wo

- sided confidence interval for the BMD Multistage Cancer Slope Factor = 0.000850453

**Parameter Estimates**
Variable Estimate Default Initial Parameter Values
Background 0.217704 0.2335
Beta(1) 0.000358397 0.000268894
Beta(2) 0 0

**Analysis of Deviance Table** 
Model Log(likelihood) # Param's Deviance Test d.f. p - value

Full model

- 112.492 4

Fitted model

- 114.97 2 4.95502 2 0.08395

Reduced model - 115.644 1 6.30404 3 0.09772

AIC: = 233.94

**Goodness of Fit**  **Table**

Dose Est. Prob. Expected Observed Size Scaled Resid

0 0.2177 10.885 8 50

- 0.989

90 0.2425 12.127 13 50 0.288

200 0.2718 13.591 19 50 1.719

420 0.327 16.351 13 50

- 1.01

Chi^2 = 5.04 d. f = 2 P- value = 0.0806

This document is a draft for review purposes only and does not constitute Agency policy. 

### C- 33 DRAFT

— DO NOT CITE OR QUOTE

### Supplemental Information― tert Butanol

**Table C-**  **15**

**. Summary of BMD modeling results for**  **r enal tubule adenoma or**  

### 1 2 3 4

5 **carcinoma in male F344 rats exposed to**  t ert

**- butanol**  **in drinking water for 2 years modeled with administered dose units and excluding high** 

**- dose group**  **( NTP, 1995**  **) ; BMR = 10% extra risk.** 

Model a Goodness of fit BMD 10Pct (mg/kg

- d) BMDL 10Pct (mg/kg

- d) Basis for model selection p value Scaled residuals AIC

Two N/A b 0.000,

- 0.000, and

- 0.000 173.6 8 75.6 41.6 Multistage 1° was selected as the only adequately

fitting model available One 0.924 0.031,

- 0.078, and 0.045 171.6 9 70.1 41.6

a Selected model in bold.
b No available degrees of freedom to calculate a goodness of fit value.



### 6

0.1 0.2 0.3 0.4 0.5

0 50 100 150 200Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

11:02 04/30 2014 BMD BMDL Multistage Cancer Linear extrapolation



### 7 8 9 10

11 **Figure C-**  **10 . Plot of incidence rate by dose, with fitted curve for selected model; dose**  **shown in mg/kg**

**- d.** 

This document is a draft for review purposes only and does not constitute Agency policy. 

### C- 34 DRAFT

— DO NOT CITE OR QUOTE

### Supplemental Information― tert Butanol

**Multistage Cancer Model.**  (Version: 1.9; Date: 05/26/2010) 

### 1 2 3 4 5 6 7 8 9 10 11 12 13 14

15 16

17 18 19 20

21 22 23 24 The form of the probability function is: P[ response] = background + (1

- background)*[1

- EXP(

- beta1*dose^1

- bet a2 *dose^2...)] The parameter betas are restricted to be positive

**Benchmark Dose Computation.** BMR = 10% Extra risk B M D = 70.1068 BMDL at the 95% confidence level = 41.5902 BMDU at the 95% confidence level = 203.311 Taken together, (41.5902, 203.311) is a 90% two

- si d ed confidence interval for the BMD Multistage Cancer Slope Factor = 0.00240441

**Parameter Estimates**
Variable Estimate Default Initial Parameter Values
Background 0.158399 0.156954
Beta(1) 0.00150286 0.0015217

**Analysis of Deviance Table**
Model Log(likelihoo d) # Param's Deviance Test d.f. p - value

Full model

- 83.8395 3

Fitted model

- 83.8441 2 0.00913685 1 0.9238

Reduced model - 86.9873 1 6.29546 2 0.04295

AIC: = 171.688

**Goodness of Fi**  **t Table** 

Dose Est. Prob. Expected Observed Size Scaled Resid

0 0.1584 7.92 8 50 0.031

90 0.2649 13.243 13 50

- 0.078

200 0.3769 18.844 19 50 0.045

Chi^2 = 0.01 d

. f = 1 P- value = 0.9239

This document is a draft for review purposes only and does not constitute Agency policy. 

### C- 35 DRAFT

— DO NOT CITE OR QUOTE

### Supplemental Information― tert Butanol

**Table C-**  **16**

**. Summary of BMD modeling results for**  **r enal tubule adenoma or**  

### 1 2 3 4

5 **carcinoma in male F344 rats exposed to**  t ert

**- butanol**  **in drinking water for 2 years modeled with PBPK (**  t ert

**- butanol**  **, mg/L) dose units and including all**  **dose groups (**  **NTP, 1995 )**  **; BMR = 10% extra risk.**

Model a Goodness of fit BMD 10Pct (mg/L) BMDL 10Pct (mg/L) Basis for model selection p value Scaled residuals AIC

Three Two One 0.051 8 - 1.373, 0.155, 1.889, and

- 0.668 234.8 3 51.8 13.9 Multistage 1° wa s selected as the
most parsimonious model of adequate fit.

a Selected model in bold.



### 6

0.1 0.2 0.3 0.4 0.5

0 10 20 30 40 50Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

11:19 04/30 2014 BMD BMDL Multistage Cancer Linear extrapolation



### 7 8 9 10

11 **Figure C-**  **11 . Plot of incidence rate by dose, with fitted curve for selected model; dose**  **shown in mg/L.**

This document is a draft for review purposes only and does not constitute Agency policy. 

### C- 36 DRAFT

— DO NOT CITE OR QUOTE

### Supplemental Information― tert Butanol

**Multistage Cancer Model.** (Version: 1.9; Date: 05/26/2010) 

### 1 2 3 4 5 6 7 8 9 10 11 12 13 14

15 16

17 18 19 20

21 22 23

24 The form of the probability function is: P[response] = background + (1

- background)*[1

- EXP(

- beta1*dose^1

- b et a2*dose^2...)] The parameter betas are restricted to be positive

**Benchmark Dose Computation.** BMR = 10% Extra risk BMD = 51.8357 BMDL at the 95% confidence level = 13.9404 BMDU at the 95% confidence level = error Taken together, (13.9404, error) is a 90% two

- s i ded confidence interval for the BMD Multistage Cancer Slope Factor = error

**Parameter Estimates**
Variable Estimate Default Initial Parameter Values
Background 0.243327 0.253053
Beta(1) 0.00203259 0.00150893

**Analysis of Deviance Table**
Model Log(likelihood) # Param's Deviance Test d.f. p - value

Full model

- 112.492 4

Fitted model

- 115.417 2 5.84883 2 0.0537

Reduced model - 115.644 1 6.30404 3 0.09772

AIC: = 234.834

**Goodness of Fi**  **t Table**

Dose Est. Prob. Expected Observed Size Scaled Resid

0 0.2433 12.166 8 50

- 1.373

4.6945 0.2505 12.526 13 50 0.155

12.6177 0.2625 13.124 19 50 1.889

40.7135 0.3034 15.171 13 50

- 0.668

Chi^2 = 5.92 d .f = 2 P- value = 0.0518

This document is a draft for review purposes only and does not constitute Agency policy. 

### C- 37 DRAFT

— DO NOT CITE OR QUOTE

### Supplemental Information― tert Butanol

**Table C-**  **17**

**. Summary of BMD modeling results for**  **r enal tubule adenoma or**  

### 1 2 3 4

5

6 7 8 9

10 **carcinoma in male F344 rats exposed to**  t ert

**- butanol**  **in drinking water for 2 years modeled with PBPK (**  t ert

**- butanol**  **, mg/L) dose units and excluding high**

  ** dose group** **( NTP, 1995**  **) ; BMR = 10% extra risk.** 

Model a Goodness of fit BMD 10Pct (mg/L) BMDL 10Pct (mg/L) Basis for model selection p value Scaled residuals AIC

Two One 0.891

- 0.054, 0.113, and

- 0.057 171.7 0 4.33 2.54 Multistage 1° was selected as the
most parsimonious model of adequate fit.

a Selected model in bold.

0.1 0.2 0.3 0.4 0.5

0 2 4 6 8 10 12Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

11:20 04/30 2014 BMD BMDL Multistage Cancer Linear extrapolation

**Fig ure**  **C- 12**  **. P lot of incidence rate by dose, with fitted curve for selected model; dose**  **shown in mg/L.**

This document is a draft for review purposes only and does not constitute Agency policy. 

### C- 38 DRAFT

— DO NOT CITE OR QUOTE

### Supplemental Information― tert Butanol

**Multistage Cancer Model.** (Version: 1.9; Date: 05/26/2010) 

### 1 2 3 4 5 6 7 8 9 10 11 12 13 14

15 16

17 18 19 20

21 22 23 24 The form of the probability function is: P[response] = background + (1

- background)*[1

- EXP(

- beta1*dose^1

- bet a2 *dose^2...)] The parameter betas are restricted to be positive

**Benchmark Dose Computation.** BMR = 10% Extra risk BMD = 4.33496 BMDL at the 95% confidence level = 2.53714 BMDU at the 95% confidence level = 12.8097 Taken together, (2.53714, 12.8097) is a 90% two

- si d ed confidence interval for the BMD Multistage Cancer Slope Factor = 0.0394144

**Parameter Estimates**
Variable Estimate Default Initial Parameter Values
Background 0.162798 0.164724
Beta(1) 0.0243048 0.0238858

**Analysis of Deviance Table**
Model Log(likelihood) # Param's Deviance Test d.f. p - value

Full model

- 83.8395 3

Fitted model

- 83.8489 2 0.0187339 1 0.8911

Reduced model - 86.9873 1 6.29546 2 0.04295

AIC: = 171.698

**Goodness of Fit**  **Table**

Dose Est. Prob. Expected Observed Size Scaled Resid

0 0.1628 8.14 8 50

- 0.054

4.6945 0.2531 12.654 13 50 0.113

12.6177 0.3839 19.195 19 50

- 0.057

Chi^2 = 0.02 d

. f = 1 P- value = 0.891

This document is a draft for review purposes only and does not constitute Agency policy. 

### C- 39 DRAFT

— DO NOT CITE OR QUOTE

### Supplemental Information― tert Butanol

**Table C-**  **18**

**. Summary of BMD modeling results for**  **r enal tubule adenoma or**  

### 1 2 3 4

5

6

7 8 9 10

11 **carcinoma in male F344 rats exposed to**  t ert

**- butanol**  **in drinking water for 2 years modeled with PBPK (metabolized, mg/hr) dose units and including all**  **dose groups (**  **NTP, 1995 )**  **; BMR = 10% extra risk.**

Model a Goodness of fit BMD 10Pct (mg/hr) BMDL 10Pct (mg/hr) Basis for model selection p value Scaled residuals AIC

Three Two One 0.088 5 - 0.920, 0.301, 1.677, and

- 1.049 233.7 6 2.28 0.954 Multistage 1° was selected as the
most parsimonious model of adequate fit.

a Selected model in bold.

Data from NTP1995

0.1 0.2 0.3 0.4 0.5

0 0.5 1 1.5 2 2.5 3 3.5Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

11:22 04/30 2014 BMD BMDL Multistage Cancer Linear extrapolation

**Fig ure**  **C- 13**  **. P lot of incidence rate by dose, with fitted curve for selected model; dose**  **shown in mg/hr.** 

This document is a draft for review purposes only and does not constitute Agency policy. 

### C- 40 DRAFT

— DO NOT CITE OR QUOTE

### Supplemental Information― tert Butanol

**Multistage Cancer Model.** (Version: 1.9; Date: 05/26/2010) 

### 1 2 3 4 5 6 7 8 9 10 11 12 13 14

15 16

17 18 19 20

21 22 23 24 The form of the probability function is: P[response] = background + (1

- background)*[1

- EXP(

- beta1*dose^1

- b et a2*dose^2...)] The parameter betas are restricted to be positive

**Benchmark Dose C omp**  **utation.** BMR = 10% Extra risk BMD = 2.28299 BMDL at the 95% confidence level = 0.95436 BMDU at the 95% confidence level = error Taken together, (0.95436, error) is a 90% two

- s i ded confidence interval for the BMD Multistage Cancer Slope Factor = error

**Parameter Estimates**
Variable Estimate Default Initial Parameter Values
Background 0.21328 0.229822
Beta(1) 0.0461502 0.0349139

**Analysis of Deviance Table**
Model Log(likelihood) # Param's Deviance Test d.f. p - value

Full model

- 112.492 4

Fitted model

- 114.879 2 4.77309 2 0.09195

Reduced model - 115.644 1 6.30404 3 0.09772

AIC: = 233.758

**Goodness of Fi**  **t Table**

Dose Est. Prob. Expected Observed Size Scaled Resid

0 0.2133 10.664 8 50

- 0.92

0.7992 0.2418 12.088 13 50 0.301

1.7462 0.2742 13.71 19 50 1.677

3.4712 0.3297 16.487 13 50

- 1.049

Chi^2 = 4.85 d .f = 2 P- value = 0.0885

This document is a draft for review purposes only and does not constitute Agency policy. 

### C- 41 DRAFT

— DO NOT CITE OR QUOTE

### Supplemental Information― tert Butanol

**Table C-**  **19**

**. Summary of BMD modeling results for**  **r enal tubule adenoma or**  

### 1 2 3 4

5

6

7 8 9 10

11 **carcinoma in male F344 rats exposed to**  t ert

**- butanol**  **in drinking water for 2 years modeled with PBPK (metabolized, mg/hr) dose units and excluding**  **high**

**- dose group**  **( NTP, 1995**  **) ; BMR = 10% extra risk.** 

Model a Goodness of fit BMD 10Pct (mg/hr) BMDL 10Pct (mg/hr) Basis for model selection p value Scaled residuals AIC

Two N/A b

- 0.000,

- 0.000, and

- 0.000 173.6 8 0.673 0.365 Multistage 1° was selected on the basis of lowest AIC. One 0.906 0.037,

- 0.096, and 0.057 171.6 9 0.614 0.364

a Selected model in bold.
b No available degrees of freedom to calculate a goodness of fit value.

Data from NTP1995

0.1 0.2 0.3 0.4 0.5

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

11:24 04/30 2014 BMD BMDL Multistage Cancer Linear extrapolation

**Fig ure**  **C- 14**  **. P lot of incidence rate by dose, with fitted curve for selected model; dose**  **shown in mg/hr.**

This document is a draft for review purposes only and does not constitute Agency policy. 

### C- 42 DRAFT

— DO NOT CITE OR QUOTE

### Supplemental Information― tert Butanol

**Multistage Cancer Model.** (Version: 1.9; Date: 05/26/2010) 

### 1 2 3 4 5 6 7 8 9 10 11 12 13 14

15 16

17 18 19 20

21 22 23 The form of the probability function is: P[response] = background + (1

- background)*[1

- EXP(

- beta1*dose^1

- b et a2*dose^2...)] The parameter betas are restricted to be positive

**Benchmark Dose Computation.** BMR = 10% Extra risk BMD = 0.613798 BMDL at the 95% confidence level = 0.364494 BMDU at the 95% confidence level = 1.77845 Taken together, (0.364494, 1.77845) is a 90% two

- s i ded confidence interval for the BMD Multistage Cancer Slope Factor = 0.274353

**Parameter Estimates**
Variable Estimate Default Initial Parameter Values
Background 0.158068 0.156284
Beta(1) 0.171653 0.174305

**Analysis of Deviance Table**
Model Log(likelihood) # Param's Deviance Test d.f. p - value

Full model

- 83.8395 3

Fitted model

- 83.8465 2 0.0138544 1 0.9063

Reduced model - 86.9873 1 6.29546 2 0.04295

AIC: = 171.693

**Goodness of Fi**  **t Table**

Dose Est. Prob. Expected Observed Size Scaled Resid

0 0.1581 7.903 8 50 0.037

0.7992 0.266 13.3 13 50

- 0.096

1.7462 0.3761 18.806 19 50 0.057

Chi^2 = 0.01 d .f = 1 P- value = 0.9064

This document is a draft for review purposes only and does not constitute Agency policy. 

### C- 43 DRAFT

— DO NOT CITE OR QUOTE

### Supplemental Information― tert Butanol

**Table C-**  **20**

**. Summary of BMD modeling results for renal tubule adenoma or**  

### 1 2 3 4

5

6 7 8 9

10 **carcinoma in male F344 rats exposed to** t ert

**- butanol**  **in drinking water for 2 years modeled with administered dose unit**  **s and including all dose g roups;**  **reanalyzed data (**  **Hard et al., 2011 ;**  **NTP, 1995 )**  **; BMR = 10% extra risk.**

Model a Goodness of fit BMD 10Pct (mg/kg

- d) BMDL 10Pct (mg/kg

- d) Basis for model

se lection p value Scaled residuals AIC

Three Two One 0.011 7 - 1.476, 1.100, 1.855, and

- 1.435 218.6 8 184 94.8 No model fit the data.

a No model was selected as a best

- fitting model.

**Table C-**  **21 . Summary of BMD modeling results for renal tubule adenoma or**  **carcinoma in male F344 rats exposed to** t er t

**- butanol**  **in drinking water for 2 years modeled with administered dose units and excluding high** 

**- dos**  **e group;**

**re -**  **a nalyzed data**  **( Hard et al.**  **, 2011 ;**  **NTP, 1995 );**  **BMR = 10% extra risk**

**.**

Model a Goodness of fit BMD 10Pct (mg/kg

- d) BMDL 10Pct (mg/kg

- d) Basis for model selection p value Scaled residuals AIC

Two One 0.572

- 0.141, 0.461, and

- 0.296 154.8 4 54.2 36.3 Multistage 1° was selected as the
most parsimonious model of adequate fit.

a Selected model in bold.

This document is a draft for review purposes only and does not constitute Agency policy. 

### C- 44 DRAFT

— DO NOT CITE OR QUOTE

### Supplemental Information― tert Butanol

1 2 3 4

5 6 7 8 9 10 11 12 13 14 15 16 17 18

19 20 0 0.1 0.2 0.3 0.4 0.5

0 50 100 150 200Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

11:05 04/30 2014 BMD BMDL Multistage Cancer Linear extrapolation

**F igure**  **C- 15**  **. Plot of incidence rate by dose, with fitted curve for selected model; dose shown in mg/kg** 

**- d.** 

**Mu ltistage Cancer Model.**  (V ersion: 1.9; Date: 05/26/2010) The form of the probability function is: P [ response] = background + (1

- background)*[1

- EXP(

- beta1*dose^1

- bet a2*dose^2...)] The parameter betas are restricted to be positive

**Benchmark Dose Computation.** BMR = 10% Extra risk BMD = 54.1642 BMDL at the 95% confidence level = 36.3321 BMDU at the 95% confidence level = 101.125 Taken together, (36.3321, 101.125) is a 90% two

- s i ded confidence interval for the BMD Multistage Cancer Slope Factor = 0.00275239

**Parameter Estimates**
Variable Estimate Default Initial Parameter Values
Background 0.0855815 0.0981146
Beta(1) 0.00194521 0.00179645

**Analysis of Deviance Table**
Model Log(likelihood) # Param's Deviance Test d.f. p - value

Full model

- 75.2622 3

Fitted model

- 75.4201 2 0.315716 1 0.5742

Reduced model - 81.4909 1 12.4574 2 0.001972

This document is a draft for review purposes only and does not constitute Agency policy. 

### C- 45 DRAFT

— DO NOT CITE OR QUOTE

### Supplemental Information― tert Butanol

1 2 3 4

5 6 7 8 AIC: = 154.84

**Goodness of F**  **it Table**

Dose Est. Prob. Expected Observed Size Scaled Resid

0 0.0856 4.279 4 50

- 0.141

90 0.2324 11.622 13 50 0.461

200 0.3803 19.015 18 50

- 0.296

Chi^2 = 0.32 d.f = 1 P- value = 0.5715

This document is a draft for review purposes only and does not constitute Agency policy. 

### C- 46 DRAFT

— DO NOT CITE OR QUOTE

### Supplemental Information― tert Butanol

**Table C-**  **22**

**. Summary of BMD modeling results for renal tubule adenoma or**  

### 1 2 3 4 5 **carcinoma in male F344 rats exposed to** t ert

**- butanol**  **in drinking water for 2 years modeled with PBPK (**  t ert

**- butanol**  **, mg/L) dose units and including all dose groups**  **; reanalyzed data (**  **Hard et al., 2011 ;**  **NTP, 1995 )**  **; BMR = 10% extra**  **risk.**

Model a Goodness of fit BMD 10Pct (mg/L) BMDL 10Pct (mg/L) Basis for model selection p value Scaled residuals AIC

Three Two One 0.004 8 - 2.089, 0.864, 2.165, and

- 0.929 220.8 2 31.4 11.7 No model fit the data.

a No model was selected as a best

- fitting model.

**Table C-**  **23**

**. Summary of BMD modeling results for renal tubule adenoma or**  

### 6 7 8 9 10 **carcinoma in male F344 rats exposed to** t ert

**- butanol**  **in drinking water for 2 years modeled with PBPK (**  t ert

**- butanol**  **, mg/L) dose units and excluding high**

  ** dose group** **; reanalyzed data**  **( Hard et al., 2011**  **; NTP, 1995**  **) ; BMR = 10% extra**  **risk.**

Model a Goodness of fit BMD 10Pct (mg/L) BMDL 10Pct (mg/L) Basis for model selection p value Scaled residuals AIC

Two One 0.364

- 0.285, 0.750, and

- 0.424 155.3 3 3.35 2.21 Multistage 1° was selected as the
most parsimonious model of adequate fit.

a Selected model in bold.

This document is a draft for review purposes only and does not constitute Agency policy. 

### C- 47 DRAFT

— DO NOT CITE OR QUOTE

### Supplemental Information― tert Butanol

1 2 3 4

5 6 7 8 9 10 11 12 13 14 15 16 17 18

19 20 0 0.1 0.2 0.3 0.4 0.5

0 2 4 6 8 10 12Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

11:30 04/30 2014 BMD BMDL Multistage Cancer Linear extrapolation

**Figure C-**  **16 . Plot of incidence rate by dose, with fitted curve for selected model; dose**  **shown in mg/L.**

**Multistage Cancer Model.** ( V ersion: 1.9; Date: 05/26/2010) The form of the probability function is: P [ response] = background + (1

- background)*[1

- EXP(

- beta1*dose^1

- bet a2*dose^2...)] The parameter betas are restricted to be positive

**Benchmark Dose Computation.** BMR = 10% Extra risk BMD = 3.34903 BMDL at the 95% confidence level = 2.20865 BMDU at the 95% confidence level = 6.49702 Ta k en together, (2.20865, 6.49702) is a 90% two

- s ided confidence interval for the BMD Multistage Cancer Slope Factor = 0.0452765

**Parameter Estimates**
Variable Estimate Default Initial Parameter Values
Background 0.0916116 0.110649
Beta(1) 0.03146 0.0276674

**Analysis of Deviance Table**
Model Log(likelihood) # Param's Deviance Test d.f. p - value

Full model

- 75.2622 3

Fitted model

- 75.664 2 0.803466 1 0.3701

Reduced model - 81.4909 1 12.4574 2 0.001972

This document is a draft for review purposes only and does not constitute Agency policy. 

### C- 48 DRAFT

— DO NOT CITE OR QUOTE

### Supplemental Information― tert Butanol

1 2 3 4

5 6

9 10 11 12 13

14 15 16 17 18

7

8 AIC: = 155.328

**Goodness of Fit**  **Table**

Dose Est. Prob. Expected Observed Size Scaled Resid

0 0.0916 4.581 4 50

- 0.285

4.6945 0.2163 10.817 13 50 0.75

12.6177 0.3892 19.462 18 50

- 0.424

Chi^2 = 0.82 d. f = 1 P- value = 0.3643

**Table C-**  **24**

**. S**  **ummary of BMD modeling results for renal tubule adenoma or carcinoma in male F344 rats exposed to**  t ert

**- bu**  **tanol in drinking water for 2**  **years modeled with PBPK (metabolized, mg/hr) dose units and including all dose groups**  **; rea**  **nalyzed data (**  **Hard et al., 2011 ;**  **NTP, 1995 )**  **; BMR = 10% extra risk.** 

Model a Goodness of fit BMD 10Pct (mg/hr) BMDL 10Pct (mg/hr) Basis for model selection p value Scaled residuals AIC

Three Two One 0.014 2 - 1.367, 1.119, 1.783, and

- 1.484 218.2 6 1.44 0.770 No model fit the data.

a No model was selected as a best

- fitting model.

**Table C-**  **25**

**. Summary of BMD modeling results for renal tubule adenoma or**  **carcinoma in male F344 rats exposed to** t ert

**- bu**  **tanol in drinking water for 2**  **years modeled with PBPK (metabolized, mg/hr) dose units and excluding high** 

**- dose group**  **; rea nalyzed data**  **( Hard et al., 2011**  **; NTP, 1995**  **); BMR = 10%**  **extra risk.**

Model a Goodness of fit BMD 10Pct (mg/hr) BMDL 10Pct (mg/hr) Basis for model selection p - value Scaled residuals AIC

Two One 0.593

- 0.130, 0.435, and

- 0.281 154.81 0.474 0.319 Multistage 1° was selected as the most parsimonious model of adequate fit.

a Selected model in bold.

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1

0 0.1 0.2 0.3 0.4 0.5

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

11:33 04/30 2014 BMD BMDL Multistage Cancer Linear extrapolation



### 2 3 4 5

6 7 8 9 10 11 12 13 14 15 16 17 18 19

20 21 **Figure C** 

**- 17**  **. Plot of incidence rate by dose, with fitted curve for selected model; dose shown in mg/hr.** 

**Multistage Cancer Model.** ( V ersion: 1.9; Date: 05/26/2010) The form of the probability function is: P [ response] = background + (1

- background)*[1

- EXP(

- beta1*dose^1

- bet a2*dose^2...)] The parameter betas are restricted to be positive

**Benchmark Dose Computation.** BMR = 10% Extra risk BMD = 0.474241 BMDL at the 95% confidence level = 0.318504 BMDU at the 95% confidence level = 0.882859 Taken together, (0.318504, 0.882859) is a 90% two

- s i ded confidence interval for the BMD Multistage Cancer Slope Factor = 0.313968

**Parameter Estimates**
Variable Estimate Default Initial Parameter Values
Background 0.0851364 0.0969736
Beta(1) 0.222167 0.206161

**Analysis of Deviance Table**
Model Log(likelihood) # Param's Deviance Test d.f. p - value

Full model

- 75.2622 3

Fitted model

- 75.4029 2 0.281435 1 0.5958

Reduced model - 81.4909 1 12.4574 2 0.001972

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1 2 3 4

5 6 7 8 AIC: = 154.806

**G oodness of**  **Fi t Table** 

Dose Est. Prob. Expected Observed Size Scaled Resid

0 0.0851 4.257 4 50

- 0.13

0.7992 0.234 11.699 13 50 0.435

1.7462 0.3793 18.966 18 50

- 0.281

Chi^2 = 0.29 d .f = 1 P- value = 0.5933

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1 2 3 **Table C-**  **26**

**. Summary of BMD modeling results for**  **thyroid follicular cell adenomas**  **in f emale**  **B6C3F1 mice**  **exposed to** t ert

**- butanol**  **in drinking water for 2 years**  **( NTP, 1995**  **) ; BMR = 10% extra risk.** 

Model a Goodness of fit BMD 10% c (mg/kg

- d) BMDL 10% c (mg/kg

- d) Basis for model selection p - v alue AIC b

Three 0.75 113.665 2002 1437 Multistage 3° was s elected on the basis of the l owest AIC with all BMDL values for fitting models being sufficiently close (BMDLs differed by less than 3

- fold)

. Two 0.36 115.402 2186 1217

One 0.63 114.115 1987 1378

a Selected (best

- fitting) model shown in boldface type
b AIC = Akaike Information Criterion

c Confidence level 0.95



### 4

0 0.05 0.1 0.15 0.2 0.25 0.3

0 50 100 150 200 250 300 350Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:51 05/13 2011 BMD BMDL Multistage Cancer Linear extrapolation



### 5

6

7 8 9 10 11 12 13 14 15 16 17 **Figure C-**  **18**

**. Plot of mean response by dose, with fitted curve for selected model.** 

==================================================================== Multistage Cancer Model. (Version: 1.9; Date: 05/26/2010)
Input Data File: M: \ NCEA 

### t ert

- butanol \ BMD modeling \ BMDS Output \ 29 NTP 1995b_Thyroid folluclar cell andenoma, female mice (HEC)_MultiCanc3_10.(d)
Gnuplot Plotting File: M: \ NCEA 

### t ert

- butanol \ BMD modeling \ BMDS Output \ 29 NTP 1995b_Thyroid folluclar cell andenoma, female mice (HEC)_MultiCanc3_10.plt Fri May 13 15:51:46 2011

=========================================== =========================

[notes]

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 The form of the probability function is:

P[response] = background + (1

- background)*[1

- EXP(

- beta1*dose^1

- beta2*dose^2

- beta3*dose^3) ]

The parameter betas are restricted to be positive

Dependent variable = Incidence Independent variable = Dose

Total number of observations = 4 Total number of records with missing values = 0 Total number of parameters in model = 4 Total number of specified parameters = 0 Degree of polynomial = 3

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e

- 008 Parameter Convergence has been set to: 1e

- 008

Default Initial Parameter Values

Background = 0.0344951

Beta(1) = 0 Beta(2) = 0 Beta(3) = 3.4555e

- 009

Asymptotic Correlation Matrix of Parameter Estimates

( *** The model parameter(s)

- Beta(1)

- Beta(2) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlation matrix )

Background Beta(3)

Background 1

- 0.54

Beta(3)

- 0.54 1

Parameter Estimates

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0359685 * * *

Beta(1) 0 * * * Beta(2) 0 * * * Beta(3) 3.30537e

- 009 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Deviance Test d.f. P- value Full model

- 54.5437 4 Fitted model

- 54.8422 2 0.597063 2 0.7419 Reduced model

- 58.5048 1 7.92235 3 0.04764

AIC: 113.684

Goodness of Fit Scaled

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------------------------------

0.0000 0.0360 2.086 2.000 58 - 0.061 83.0000 0.0378 2.267 3.000 60 0.496 164.0000 0.0499 2.945 2.000 59 - 0.565 334.0000 0.1477 8.713 9.000 59 0.105

Chi^2 = 0.58 d.f. = 2 P- value = 0.7482

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 317.068

BMDL = 228.888

BMDU = 600.031

Taken together, (228.888, 600.031) is a 90 % two

- sided confidence interval for the BMD

Multistage Cancer Slope Factor = 0.000436894

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# APPENDIX D. SUMMARY OF EXTERNAL PEER 1

2

3

4

5

6
7

8

9

10

11
12 

# REVIEW AND PUBLIC COMMENTS AND EPA’S DISPOSITION

[placeholder]

**Additional Appendices:**

[appendices can be used to supplement the HI and D

- R analysis – the information presented by the appendices will be chemical

- specific]

**Examples:**

• **PBPK Modeling of [**  **chemical ]**  **and metabolites –**  **detailed methods and results**

• **Meta**

**- analysis of ________**  **results from epidemiological studies**

• **Lifetable analysis and weighted linear regression based on results from [reference]** 

This document is a draft for review purposes only and does not constitute Agency policy. 

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1

2

3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 

# REFERENCES FOR APPENDICES

ACGIH (American Conference of Governmental Industrial Hygienists). (2012). Documentation of the threshold limit values and biological exposure indi ces tert

- Butanol (7th ed.). Cincinnati, OH. Amberg, A; Rosner, E; Dekant, W. (1999). Biotransformation and kinetics of excretion of methyl

tert

- butyl ether in rats and humans. Toxicol Sci 51: 1

- 8. Amberg, A; Rosner, E; Dekant, W. (2000). Biotransformation and kinetics of excretion of ethyl
tert

- butyl ether in rats and humans. Toxicol Sci 53: 194

- 201. http://dx.doi.org/10.1093/toxsci/53.2.194 Andersen, ME. (1991). Physio logical modelling of organic compounds. Ann Occup Hyg 35: 309

- 321. ARCO (ARCO Chemical Company). (1983). Toxicologist's report on metabolism and pharmacokinet ics of radiolabeled TBA 534 tertiary butyl alcohol with cover letter dated 03/24/1994. (8EHQ86940000263). Newton Square, PA. Arslanian, MJ; Pascoe, E; Reinhold, JG. (1971). Rat liver alcohol dehydrogenase. Purification and properties. Biochem J 125: 1039

- 1047. ATSDR (Agency for Toxic Substances and Disease Regist ry). (1996). Toxicological profile for methyl

- tert

- butyl ether [ATSDR Tox Profile]. Atlanta, GA: U.S. Department of Health and Human Services, Public Health Service. http://www.atsdr.cdc.gov/toxprofiles/tp.asp?id=228&tid=41 Baker, RC; Sorensen, SM; Deitrich, RA. (1982). The in vivo metabolism of tertiary butanol by adult rats. Alcohol Clin Exp Res 6: 247

- 251. http://dx.doi.org/10.1111/j.1530

- 0277.1982.tb04970.x Bernauer, U; Amberg, A; Scheutzow, D; Dekant, W. (1998). Biotransformation of 12C - and 2

- 13C

- labeled methyl tert

- butyl ether, ethyl tert

- butyl ether, and tert

- butyl alcohol in rats: identification of metabolites in urine by 13C nuclear magnetic resonance and gas chromatography/mass spectrometry. Chem Res Toxicol 11: 651

- 658. http://dx.doi.org/10.1021/tx970215v Blancato, JN; Evans, MV; Power, FW; Caldwell, JC. (2007). Development and use of PBPK modeling and the impact of metabolism on variability in dose metrics for the risk assessment of methyl tertiary butyl ether (MTBE). J Environ Prot Sci 1: 29

- 51. Borghoff, S; Murphy, J; Medinsky, M. (1996). Development of physiologically based pharmacokinetic model for me thyl tertiary

- butyl ether and tertiary

- butanol in male Fisher

- 344 rats. Fundam Appl Toxicol 30: 264

- 275. http://dx.doi.org/10.1006/faat.1996.0064 Borghoff, S; Parkinson, H; Leavens, T. (2010). Physiologically based pharmacokinetic rat model for methyl tertiary

- butyl ether; comparison of selected dose metrics following various

This document is a draft for review purposes only and does not constitute Agency policy. 

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MT BE exposure scenarios used for toxicity and carcinogenicity evaluation. Toxicology 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 275: 79

- 91. http://dx.doi.org/10.1016/j.tox.2010.06.003 Borghoff, SJ; Prescott, JS; Janszen, DB; Wong, BA; Everitt, JI. (2001). alpha2u

- Globulin nephropathy, renal cell proliferation, and dosimetry of inhaled tert

- butyl alcohol in male and female F

- 344 rats. Toxicol Sci 61: 176

- 186. Borghoff, SJ; Short, BG; Swenberg, JA. (1990). Biochemical mechanisms and pathobiology of alpha 2u

- globulin nephropathy [Review]. Annu Rev Pharmacol Toxicol 30: 349

- 367. http://dx.doi.org/10.1146/annurev.pa.30.040190.002025 Brown, MA; Cornell, BA; Davenport, JB. (1977) . PERTURBATION OF BIOLOGICAL

- MEMBRANES WITH TERT

- BUTANOL. Seikagaku 49: 1

- 1. Cederbaum, AI; Cohen, G. (1980). Oxidative demethylation of t

- butyl alcohol by rat liver microsomes. Biochem Biophys Res Commun 97: 730

- 736. Cederbaum, AI; Qureshi, A; Cohen, G. (1983). Production of formaldehyde and acetone by hydroxyl

- radic al generating systems during the metabolism of tertiary butyl alcohol. Biochem Pharmacol 32: 3517

- 3524. http://dx.doi.org/10.1016/0006

- 2952(83)90297 -6 Dickey, FH; Cleland, GH; Lotz, C. (1949). The role of organic peroxides in the induction of mutations. PNAS 35: 581

- 586. Faulkner, T; Hussain, A. (1989). The pharmacokinetics of tertiary butanol in C57BL/6J mice. Res Comm Chem Pathol Pharmacol 64: 31

- 39. Faulkner, TP ; Wiechart, JD; Hartman, DM; Hussain, AS. (1989). The effects of prenatal tertiary butanol administration in CBA/J and C57BL/6J mice. Life Sci 45: 1989

- 1995. FDA (U.S. Food and Drug Administration). (2011a). Indirect food additives: Adjuvants, production aids, and sanitizers. Surface lubricants used in the manufacture of metallic articles. 21 CFR 178.3910. http://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfcfr/CFRSearch.cfm?fr=178.3910
FDA (U.S. Food and Drug Administration). (2011b). Indirect food additives: Paper and paperboard components. Defoaming agents used in coatings. 21 CFR 176.200. http://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfcfr/CFRSearch.cfm?fr=176.200 Hard, GC; Bruner, RH; Cohen, SM; Pletcher, JM; Regan, KS. (201 1). Renal histopathology in toxicity and carcinogenicity studies with tert

- butyl alcohol administered in drinking water to F344 rats: A pathology working group review and re

- evaluation. Regul Toxicol Pharmacol 59: 430

- 436. http://dx.doi.org/10.1016/j.yrtph.2011.01.007 Jimenez, J; Longo, E; Benitez, T. (1988). Induction of petite yeast mutants by membran e- active agents. Appl Environ Microbiol 54: 3126

- 3132. Johanson, G; Nihlén, A; Lof, A. (1995). Toxicokinetics and acute effects of MTBE and ETBE in male volunt eers. Toxicol Lett 82/83: 713

- 718. http://dx.doi.org/10.1016/0378

- 4274(95)03589 -3 Kim, D; Andersen, ME; Pleil, JD; Nylander

- French, LA; Prah, JD. (2007). Refined PBPK model of aggregate exposure to methyl tertiary

- butyl ether. Toxicol Lett 169: 222

- 235. http://dx.doi.org/10.1016/j.toxlet.2007.01.008 Leavens, T; Borghoff, S. (2009). Physiologically based pharmacokinetic model of methyl tertiary butyl ether and tertiary butyl alcohol dosimetry in mal e rats based on binding to alpha2u

- globulin. Toxicol Sci 109: 321

- 335. http://dx.doi.org/10.1093/toxsci/kfp049

This document is a draft for review purposes only and does not constitute Agency policy. 

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### Supplemental Information― tert Butanol

Licata, AC; Dekant, W; Smith, CE; Borghoff, SJ. (2001). A physiologically based pharmacokinetic 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 model for methyl tert

- butyl ether in humans: Implementing sensitivity and variability analyses. Toxicol Sci 62: 191

- 204. http://dx.doi.org/10.1093/toxsci/62.2.191 Mcgregor, D; Cruzan, G; Callander, R; May, K; Banton, M. (2005). The mutagenicity testing of
te rtiary

- butyl alcohol, tertiary

- butyl acetate and methyl tertiary

- butyl ether in Salmonella typhimurium. Mutat Res 565: 181

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- butyl ether in human s. Toxicol Sci 51: 184

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butyl ethers, t

- amyl methyl ether, and t

- butyl alcohol. J Expo Anal Environ Epidemiol 5: 573

- 582. Nihlén, A; Lof, A; Johanson, G. (1998a). Controlled ethyl tert

- butyl ether (ETBE) exposure of male volunteers: I Toxicokinetics. Toxicol Sci 46: 1

- 10. http://dx.doi.org/10.1006/toxs.1998.2516 Nihlén, A; Lof, A; Johanson, G. (1998b). Experimental exposure to methyl tertiary

- butyl ether: I Toxicokinetics in humans. Toxicol Appl Pharmacol 148: 274

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- 149). Cincinnati, OH. http://www.cdc.gov/niosh/docs/2005

- 149/ NSF International. (2003). t

- Butanol: Oral Risk Assessment Document (CAS 75

- 65

- 0). A nn Arbor, MI. NTP (National Toxicology Program). (1995). Toxicology and carcinogenesis studies of t

- butyl alcohol (CAS no 75

- 65

- 0) in F344/N rats and B6C3F1 mi ce (Drinking water studies) (pp. 1- 305). (NTPTR436). Research Triangle Park, NC.
NTP (National Toxicology Program). (1997). NTP technical report on toxicity st udies of t

- butyl alcohol (CAS no 75

- 65

- 0) administered by inhalation to F344/N rats and B6C3F1 mice (pp. 1

- 56, A51

- D59). Research Triangle Park, NC. http://ntp.niehs.nih.gov/ntp/htdocs/ST_rpts/tox053.pdf OSHA (Occupational Safety & Health Administration). (2006). Table Z

- 1 limits for air contaminants. Occupational safety and health standards, subpart Z, toxic and hazardous substances. (OSHA standard 1910.1000). Washington, DC: U.S. Department of Labor. http://www.osha.gov/pls/oshaweb/owadisp.show_docu ment?p_table=STANDARDS&p_ id=9992 Poet, TS; Valentine, JL; Borghoff, SJ. (1997). Pharmacokinetics of tertiary butyl alcohol in male and female Fischer 344 rats. Toxicol Lett 92: 179

- 186. Prah, J; Ashley, D; Blount, B; Case, M; Leavens, T; Pleil, J; Cardinali, F. (2004). Dermal, oral, and inhalation pharmacokinetics of methyl tertiary butyl ether (MTBE) in human volunteers. Toxicol Sci 77: 195

- 205. http://dx.doi.org/10.1093/toxsci/kfh009

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Rao, HV; Ginsberg, GL. (1997). A physiologically

- based pharmacokinetic model assessment of 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 methyl t

- butyl ether in groundwater for a bathing and showering determination. Risk Anal 17: 583

- 598. Sgambato, A; Iavicoli, I; De Paola, B; Bianchino, G; Boninsegna, A; Bergamaschi, A; Pietroiusti, A; Cittadini, A. (2009). Differential toxic effects of methyl tertiary butyl ether and tert

butanol on rat fi broblasts in vitro. Toxicol Ind Health 25: 141

- 151. http://dx.doi.org/10.1177/0748233709104867 Spiteri, N J. (1982). Circadian patterning of feeding, drinking and activity during diurnal food access in rats. Physiol Behav 28: 139

- 147. http://dx.doi.org/10.1016/0031

- 9384(82)90115 -9 Tang, G; Wang, J; Zhuang, Z. (1997). [Cytotoxicity and genotoxicity of methyl tert

- butyl ether and its metabolite to human leukemia cells]. Zhonghua Yufang Yixue Zazhi 3 1: 334

- 337. U.S. EPA (U.S. Environmental Protection Agency). (2000). Benchmark dose technical guidance document [external review draft] [EPA Report]. (EPA/630/ R- 00/001). Washington, DC: U.S. Environmental Protection Agency, Risk Assessment Forum. http://www.epa.gov/raf/publications/benchmark

- dose

- doc

- draft.htm Videla, LA; Fernández, V; de Marinis, A; Fernández, N; Valenzuela, A. (1982). Liver lipoperoxidative pressure and glutathione status following acetaldehyde and aliphatic alcohols pret reatments in the rat. Biochem Biophys Res Commun 104: 965

- 970. http://dx.doi.org/10.1016/0006

- 291X(82)91343 -2 Williams

- Hill, D; Spears, CP; Prakash, S; Olah, GA; Shamma, T; Moin, T; Kim, LY; Hill, CK. (1999). Mutagenicity studies of methyl

- tert

- butylether using the Ames tester strain TA102. Mutat Res 446: 15

- 21. http://dx.doi.org/10.1016/s1383

- 5718(99)00137 -0 Williams, TM; Borghoff, SJ. (2001). Characterization of tert

- butyl alcohol binding to "alpha "2u

globulin in F

- 344 rats. Toxicol Sci 62: 228

- 235. Yuan, Y; Wang, HF; Sun, HF; Du, HF; Xu, LH; Liu, YF; Ding, XF; Fu, DP; Liu, KX. (2007). Adduction of DNA with MTBE and TBA in mice studied by accelerator mass Spectrometry. Environ Toxicol 22: 630

- 635. http://dx.doi.org/10.1002/tox.20295 Zeiger, E; Anderson, B; Haworth, S; Lawlor, T; Mortelmans, K; Speck, W. (1987). Salmonella mutagenicity tests: III. Results from the testing of 255 chemicals. Environ Mutagen 9: 1

- 60. http://dx.doi.org/10.1002/em.2860090602

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